In Study 1, adults with strong religious commitments and faith practices were interviewed in depth about their spiritual experiences and their understanding of the mind by experienced ethnographers. These interviews yielded one measure of porosity (“Porosity Vignettes”), one measure of absorption (the Absorption scale), and one measure of spiritual experience (“Spiritual Events” scale).
This notebook contains all of the analyses for Study 1 (revised July 2020).
source("../scripts_general/dependencies.R")
package ‘ggplot2’ was built under R version 4.0.2package ‘tibble’ was built under R version 4.0.2package ‘dplyr’ was built under R version 4.0.2package ‘stargazer’ was built under R version 4.0.1package ‘kableExtra’ was built under R version 4.0.2package ‘htmltools’ was built under R version 4.0.2package ‘svglite’ was built under R version 4.0.2
source("../scripts_general/custom_funs.R")
source("../scripts_general/var_recode_contrast.R")
source("../scripts_general/data_load.R")
# get item-level question
d1_byq <- read_csv("./data_byquestion/study1_byquestion.csv")
Parsed with column specification:
cols(
.default = col_double(),
study = col_character(),
date = col_date(format = ""),
researcher = col_character(),
country = col_character(),
site = col_character(),
religion = col_character(),
subject_gender = col_character(),
subject_job = col_character(),
subject_schedule = col_character(),
subject_livedhere = col_character(),
subject_lang = col_character(),
subject_marital = col_character(),
subject_hs = col_character(),
subject_liveswith = col_character(),
servicesperweek = col_character()
)
See spec(...) for full column specifications.
d3_byq <- read_csv("./data_byquestion/packets123_data_byquestion_long.csv") %>%
filter(packet == 1)
Parsed with column specification:
cols(
packet = col_double(),
version = col_double(),
subj = col_double(),
ctry = col_character(),
wher = col_character(),
recr = col_character(),
whoc = col_character(),
question = col_character(),
response = col_double()
)
d4_byq <- read_csv("./data_byquestion/study4_byquestion.csv")
Missing column names filled in: 'X1' [1]Parsed with column specification:
cols(
.default = col_double(),
p7_ctry = col_character(),
p7_abs_check = col_character(),
p7_dse_check = col_character(),
p7_se_check = col_character(),
p7_unev_check = col_character(),
p7_exsen_check = col_character(),
p7_por_check = col_character(),
p7_mm_check = col_character(),
p7_dem_sex = col_character(),
p7_dem_pocc = col_character(),
p7_dem_major = col_character(),
p7_dem_ethnicity = col_character(),
p7_dem_rur.urb = col_character(),
p7_dem_affrd.basics = col_character(),
p7_dem_religion = col_character(),
p7_dem_church = col_character(),
p7_dem_holy.tung.gif = col_character(),
p7_abs_child.exp_cat = col_logical(),
p7_abs_poetic_cat = col_logical(),
p7_abs_tv.real_cat = col_logical()
# ... with 162 more columns
)
See spec(...) for full column specifications.
# dataframe with variable names optimized for stargazer tables
d1_fortab <- d1 %>%
mutate_at(vars(ends_with("_score"), subject_age), scale) %>%
mutate(subject_hs = case_when(is.na(subject_hs) ~ NA_character_,
grepl("yes", tolower(subject_hs)) ~ "yes",
TRUE ~ "no"),
subject_hs = factor(subject_hs,
levels = c("no", "yes")),
subject_gender = factor(subject_gender,
levels = c("Female", "Male"))) %>%
rename("Spiritual Events" = "spev_score",
"Spiritual Events, recoded" = "spev_recoded_score",
"Porosity Vignettes" = "pv_score",
"Absorption" = "abs_score",
"Country" = "country",
"Site" = "site",
"Religion" = "religion",
"Gender" = "subject_gender",
"Age" = "subject_age",
"Education" = "subject_hs")
# set contrasts
contrasts(d1_fortab$Country) <- cbind(": Gh." = c(-1, 1, 0, 0, 0),
": Th." = c(-1, 0, 1, 0, 0),
": Ch." = c(-1, 0, 0, 1, 0),
": Va." = c(-1, 0, 0, 0, 1))
contrasts(d1_fortab$Site) <- cbind(": rural" = c(-1, 1))
contrasts(d1_fortab$Religion) <- cbind(": CC" = c(1, -1))
contrasts(d1_fortab$Education) <- cbind(": at least HS" = c(-1, 1))
contrasts(d1_fortab$Gender) <- cbind(": male" = c(-1, 1))
# dataframe with variable names optimized for stargazer tables
d3_fortab <- d3 %>%
mutate_at(vars(ends_with("_score"), subject_age), scale) %>%
mutate(subject_gender = factor(subject_gender,
levels = c("female", "male"))) %>%
rename("Spiritual Events" = "spev_score",
"Daily Spiritual Experiences" = "dse_score",
"Absorption" = "abs_score",
"Country" = "country",
"Gender" = "subject_gender",
"Age" = "subject_age")
# set contrasts
contrasts(d3_fortab$Country) <- cbind(": Gh." = c(-1, 1, 0, 0, 0),
": Th." = c(-1, 0, 1, 0, 0),
": Ch." = c(-1, 0, 0, 1, 0),
": Va." = c(-1, 0, 0, 0, 1))
contrasts(d3_fortab$Gender) <- cbind(": male" = c(-1, 1))
# dataframe with variable names optimized for stargazer tables
d4_fortab <- d4 %>%
mutate_at(vars(ends_with("_score"), subject_age), scale) %>%
mutate(subject_gender = factor(subject_gender,
levels = c("female", "male"))) %>%
rename("Spiritual Events" = "spev_score",
"Daily Spiritual Experience" = "dse_score",
"Porosity Vignettes" = "pv_score",
"Porosity Scale" = "por_score",
"Absorption" = "abs_score",
"Hallucinations" = "hall_score",
"Paranormal" = "para_score",
"Need for Cognition" = "cog_score",
"Sense of Control" = "ctl_score",
"Country" = "country",
"Gender" = "subject_gender",
"Age" = "subject_age")
# set contrasts
contrasts(d4_fortab$Country) <- cbind(": Gh." = c(-1, 1, 0, 0, 0),
": Th." = c(-1, 0, 1, 0, 0),
": Ch." = c(-1, 0, 0, 1, 0),
": Va." = c(-1, 0, 0, 0, 1))
contrasts(d4_fortab$Gender) <- cbind(": male" = c(-1, 1))
“I can often somehow sense the presence of another person before I actually see or hear her/him.” “At times I somehow feel the presence of someone who is not physically there”
d1_abs_omit <- d1_byq %>%
select(subject_id, country, ends_with("_abs")) %>%
select(-sensepresence_abs, -invisiblepresence_abs) %>%
gather(question, response, -subject_id, -country) %>%
group_by(subject_id, country) %>%
summarise(Absorption = mean(response, na.rm = T)) %>%
ungroup() %>%
group_by(country) %>%
mutate(Absorption = scale(Absorption)) %>%
ungroup() %>%
distinct(subject_id, Absorption) %>%
right_join(d1_fortab %>% select(-Absorption)) %>%
filter(subject_id %in% d1_fortab$subject_id)
`summarise()` has grouped output by 'subject_id'. You can override using the `.groups` argument.
Joining, by = "subject_id"
r04_spev <- lm(`Spiritual Events` ~ `Porosity Vignettes`,
data = d1_abs_omit)
r05_spev <- lm(`Spiritual Events` ~ Absorption,
data = d1_abs_omit)
r06_spev <- lm(`Spiritual Events` ~ `Porosity Vignettes` * Absorption,
data = d1_abs_omit)
r07_spev <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`,
data = d1_abs_omit)
r08_spev <- lm(`Spiritual Events` ~ Country * Site * Religion
+ Absorption + Country:Absorption,
data = d1_abs_omit)
r09_spev <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ Absorption + Country:Absorption
+ `Porosity Vignettes`:Absorption
+ Country:`Porosity Vignettes`:Absorption,
data = d1_abs_omit)
r10_spev <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ Absorption + Country:Absorption
+ `Porosity Vignettes`:Absorption
+ Country:`Porosity Vignettes`:Absorption
+ Gender + Age + Education,
data = d1_abs_omit)
table_s20 <- stargazer(r04_spev, r05_spev, r06_spev,
r07_spev, r08_spev, r09_spev, r10_spev,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^Absorption$",
"^`Porosity Vignettes`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20),
file = "./stargazer_tables/table_s20.html")
htmltools::includeHTML("./stargazer_tables/table_s20.html")
| Spiritual Events | |||||||
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | |
| Porosity Vignettes | 0.36 (0.26, 0.47) | 0.33 (0.22, 0.43) | 0.36 (0.23, 0.48) | 0.32 (0.18, 0.47) | 0.30 (0.16, 0.44) | ||
| p = 0.00 | p = 0.00 | p = 0.0000001 | p = 0.00002 | p = 0.0001 | |||
| Absorption | 0.19 (0.08, 0.30) | 0.13 (0.02, 0.24) | 0.27 (0.17, 0.36) | 0.23 (0.12, 0.35) | 0.24 (0.12, 0.36) | ||
| p = 0.001 | p = 0.02 | p = 0.0000001 | p = 0.0002 | p = 0.0001 | |||
| Porosity Vignettes × Absorption | -0.06 (-0.16, 0.05) | -0.02 (-0.17, 0.13) | -0.04 (-0.19, 0.11) | ||||
| p = 0.31 | p = 0.81 | p = 0.61 | |||||
| Country: Gh. | 0.01 (-0.21, 0.23) | 0.15 (-0.02, 0.31) | 0.10 (-0.13, 0.32) | 0.09 (-0.14, 0.32) | |||
| p = 0.92 | p = 0.08 | p = 0.41 | p = 0.46 | ||||
| Country: Th. | -0.14 (-0.37, 0.08) | -0.04 (-0.25, 0.16) | -0.12 (-0.34, 0.10) | -0.12 (-0.35, 0.11) | |||
| p = 0.21 | p = 0.69 | p = 0.31 | p = 0.31 | ||||
| Country: Ch. | -0.17 (-0.42, 0.08) | -0.41 (-0.60, -0.22) | -0.25 (-0.55, 0.05) | -0.25 (-0.55, 0.05) | |||
| p = 0.18 | p = 0.00003 | p = 0.11 | p = 0.10 | ||||
| Country: Va. | 0.70 (0.51, 0.90) | 0.80 (0.59, 1.00) | 0.68 (0.46, 0.90) | 0.65 (0.40, 0.89) | |||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.0000004 | ||||
| Site: rural | 0.01 (-0.08, 0.10) | 0.04 (-0.05, 0.14) | 0.05 (-0.05, 0.14) | 0.04 (-0.08, 0.15) | |||
| p = 0.79 | p = 0.40 | p = 0.35 | p = 0.53 | ||||
| Religion: CC | 0.24 (0.15, 0.34) | 0.27 (0.18, 0.37) | 0.25 (0.16, 0.35) | 0.25 (0.16, 0.35) | |||
| p = 0.0000005 | p = 0.0000001 | p = 0.0000004 | p = 0.000001 | ||||
| Gender: male | -0.06 (-0.15, 0.03) | ||||||
| p = 0.21 | |||||||
| Age | -0.09 (-0.19, 0.02) | ||||||
| p = 0.11 | |||||||
| Education: at least HS | -0.12 (-0.29, 0.06) | ||||||
| p = 0.20 | |||||||
| Country: Gh. × Site: rural | -0.26 (-0.43, -0.10) | -0.24 (-0.40, -0.07) | -0.27 (-0.44, -0.11) | -0.23 (-0.41, -0.06) | |||
| p = 0.002 | p = 0.01 | p = 0.002 | p = 0.01 | ||||
| Country: Th. × Site: rural | -0.03 (-0.24, 0.18) | -0.03 (-0.24, 0.17) | -0.03 (-0.23, 0.18) | -0.01 (-0.22, 0.20) | |||
| p = 0.77 | p = 0.76 | p = 0.80 | p = 0.94 | ||||
| Country: Ch. × Site: rural | 0.43 (0.24, 0.62) | 0.49 (0.29, 0.69) | 0.48 (0.28, 0.68) | 0.44 (0.23, 0.65) | |||
| p = 0.00002 | p = 0.000002 | p = 0.000003 | p = 0.0001 | ||||
| Country: Va. × Site: rural | 0.06 (-0.13, 0.25) | -0.03 (-0.24, 0.18) | 0.02 (-0.20, 0.24) | -0.01 (-0.23, 0.22) | |||
| p = 0.53 | p = 0.77 | p = 0.86 | p = 0.95 | ||||
| Country: Gh. × Religion: CC | -0.17 (-0.33, 0.001) | -0.15 (-0.32, 0.02) | -0.12 (-0.29, 0.05) | -0.11 (-0.31, 0.09) | |||
| p = 0.06 | p = 0.08 | p = 0.17 | p = 0.31 | ||||
| Country: Th. × Religion: CC | -0.18 (-0.39, 0.04) | -0.11 (-0.32, 0.09) | -0.16 (-0.37, 0.05) | -0.16 (-0.38, 0.06) | |||
| p = 0.11 | p = 0.29 | p = 0.14 | p = 0.16 | ||||
| Country: Ch. × Religion: CC | -0.16 (-0.35, 0.03) | -0.12 (-0.31, 0.08) | -0.10 (-0.29, 0.09) | -0.13 (-0.32, 0.06) | |||
| p = 0.11 | p = 0.25 | p = 0.32 | p = 0.20 | ||||
| Country: Va. × Religion: CC | 0.21 (0.02, 0.40) | 0.12 (-0.09, 0.33) | 0.12 (-0.09, 0.33) | 0.14 (-0.07, 0.35) | |||
| p = 0.03 | p = 0.26 | p = 0.25 | p = 0.21 | ||||
| Site: rural × Religion: CC | -0.07 (-0.17, 0.02) | -0.13 (-0.23, -0.04) | -0.11 (-0.21, -0.02) | -0.13 (-0.23, -0.04) | |||
| p = 0.12 | p = 0.01 | p = 0.03 | p = 0.01 | ||||
| Country: Gh. × Porosity Vignettes | -0.20 (-0.39, -0.001) | -0.25 (-0.46, -0.04) | -0.23 (-0.44, -0.03) | ||||
| p = 0.05 | p = 0.02 | p = 0.03 | |||||
| Country: Th. × Porosity Vignettes | -0.07 (-0.32, 0.17) | -0.06 (-0.31, 0.19) | -0.04 (-0.30, 0.21) | ||||
| p = 0.56 | p = 0.65 | p = 0.74 | |||||
| Country: Ch. × Porosity Vignettes | -0.03 (-0.27, 0.22) | -0.08 (-0.36, 0.20) | -0.05 (-0.34, 0.23) | ||||
| p = 0.84 | p = 0.57 | p = 0.72 | |||||
| Country: Va. × Porosity Vignettes | 0.40 (0.06, 0.73) | 0.51 (0.10, 0.92) | 0.45 (0.03, 0.86) | ||||
| p = 0.03 | p = 0.02 | p = 0.04 | |||||
| Country: Gh. × Absorption | 0.11 (-0.08, 0.30) | 0.16 (-0.05, 0.38) | 0.16 (-0.05, 0.38) | ||||
| p = 0.26 | p = 0.15 | p = 0.14 | |||||
| Country: Th. × Absorption | 0.04 (-0.15, 0.22) | 0.09 (-0.11, 0.30) | 0.08 (-0.12, 0.29) | ||||
| p = 0.69 | p = 0.38 | p = 0.43 | |||||
| Country: Ch. × Absorption | 0.04 (-0.16, 0.24) | -0.03 (-0.34, 0.28) | -0.05 (-0.36, 0.26) | ||||
| p = 0.71 | p = 0.84 | p = 0.77 | |||||
| Country: Va. × Absorption | -0.05 (-0.26, 0.15) | -0.06 (-0.27, 0.15) | -0.05 (-0.26, 0.16) | ||||
| p = 0.61 | p = 0.60 | p = 0.66 | |||||
| Country: Gh. × Site: rural × Religion: CC | -0.12 (-0.28, 0.04) | -0.21 (-0.39, -0.03) | -0.23 (-0.41, -0.05) | -0.24 (-0.42, -0.06) | |||
| p = 0.16 | p = 0.03 | p = 0.02 | p = 0.02 | ||||
| Country: Th. × Site: rural × Religion: CC | 0.21 (-0.001, 0.42) | 0.30 (0.09, 0.51) | 0.25 (0.05, 0.46) | 0.25 (0.04, 0.46) | |||
| p = 0.06 | p = 0.01 | p = 0.02 | p = 0.03 | ||||
| Country: Ch. × Site: rural × Religion: CC | -0.16 (-0.35, 0.03) | -0.08 (-0.27, 0.12) | -0.09 (-0.28, 0.10) | -0.09 (-0.28, 0.10) | |||
| p = 0.11 | p = 0.44 | p = 0.38 | p = 0.37 | ||||
| Country: Va. × Site: rural × Religion: CC | 0.05 (-0.15, 0.24) | -0.02 (-0.23, 0.19) | 0.05 (-0.16, 0.26) | 0.07 (-0.15, 0.28) | |||
| p = 0.65 | p = 0.86 | p = 0.64 | p = 0.55 | ||||
| Country: Gh. × Porosity Vignettes × Absorption | -0.06 (-0.26, 0.14) | -0.08 (-0.27, 0.12) | |||||
| p = 0.55 | p = 0.46 | ||||||
| Country: Th. × Porosity Vignettes × Absorption | -0.17 (-0.41, 0.07) | -0.18 (-0.42, 0.06) | |||||
| p = 0.16 | p = 0.14 | ||||||
| Country: Ch. × Porosity Vignettes × Absorption | -0.03 (-0.33, 0.28) | 0.01 (-0.30, 0.31) | |||||
| p = 0.87 | p = 0.97 | ||||||
| Country: Va. × Porosity Vignettes × Absorption | 0.31 (-0.17, 0.79) | 0.26 (-0.21, 0.74) | |||||
| p = 0.21 | p = 0.29 | ||||||
| Constant | -0.01 (-0.12, 0.09) | -0.01 (-0.12, 0.10) | -0.01 (-0.11, 0.10) | 0.03 (-0.08, 0.14) | 0.01 (-0.08, 0.11) | 0.04 (-0.07, 0.16) | 0.09 (-0.05, 0.23) |
| p = 0.79 | p = 0.82 | p = 0.93 | p = 0.62 | p = 0.79 | p = 0.47 | p = 0.20 | |
| Observations | 318 | 301 | 297 | 318 | 301 | 297 | 293 |
| R2 | 0.13 | 0.04 | 0.14 | 0.46 | 0.45 | 0.50 | 0.52 |
| Adjusted R2 | 0.13 | 0.03 | 0.13 | 0.42 | 0.40 | 0.44 | 0.45 |
| Residual Std. Error | 0.94 (df = 316) | 0.97 (df = 299) | 0.92 (df = 293) | 0.77 (df = 293) | 0.76 (df = 276) | 0.74 (df = 262) | 0.74 (df = 255) |
| F Statistic | 48.40*** (df = 1; 316) | 11.87*** (df = 1; 299) | 16.20*** (df = 3; 293) | 10.38*** (df = 24; 293) | 9.39*** (df = 24; 276) | 7.73*** (df = 34; 262) | 7.43*** (df = 37; 255) |
r11_spev <- lmer(`Spiritual Events` ~ 1
+ (1 | Country/Site/Religion),
control = lmerControl(optimizer = "bobyqa"),
data = d1_abs_omit)
boundary (singular) fit: see ?isSingular
r12_spev <- lmer(`Spiritual Events` ~ `Porosity Vignettes`
# + (1 + `Porosity Vignettes` | Country/Site/Religion),
+ (1 | Country/Site/Religion),
control = lmerControl(optimizer = "bobyqa"),
data = d1_abs_omit)
boundary (singular) fit: see ?isSingular
r13_spev <- lmer(`Spiritual Events` ~ Absorption
# + (1 + Absorption | Country/Site/Religion),
+ (1 | Country/Site/Religion),
control = lmerControl(optimizer = "bobyqa"),
data = d1_abs_omit)
boundary (singular) fit: see ?isSingular
r14_spev <- lmer(`Spiritual Events` ~ `Porosity Vignettes` * Absorption
# + (1 + `Porosity Vignettes` * Absorption | Country/Site/Religion),
# + (1 + `Porosity Vignettes` + Absorption | Country/Site/Religion),
+ (1 | Country/Site/Religion),
control = lmerControl(optimizer = "bobyqa"),
data = d1_abs_omit)
r15_spev <- lmer(`Spiritual Events` ~ `Porosity Vignettes` * Absorption
+ Gender + Age + Education
# + (1 + `Porosity Vignettes` * Absorption | Country/Site/Religion),
# + (1 + `Porosity Vignettes` + Absorption | Country/Site/Religion),
+ (1 | Country/Site/Religion),
control = lmerControl(optimizer = "bobyqa"),
data = d1_abs_omit)
boundary (singular) fit: see ?isSingular
htmltools::includeHTML("./stargazer_tables/table_s21.html")
| Spiritual Events | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.29 (0.18, 0.40) | 0.22 (0.11, 0.34) | 0.21 (0.10, 0.32) | ||
| p = 0.0000002 | p = 0.0001 | p = 0.0002 | |||
| Absorption | 0.25 (0.16, 0.34) | 0.20 (0.11, 0.30) | 0.20 (0.11, 0.29) | ||
| p = 0.0000002 | p = 0.00002 | p = 0.00003 | |||
| Porosity Vignettes × Absorption | -0.04 (-0.13, 0.05) | -0.06 (-0.15, 0.03) | |||
| p = 0.43 | p = 0.23 | ||||
| Gender: male | -0.05 (-0.14, 0.04) | ||||
| p = 0.30 | |||||
| Age | -0.09 (-0.19, 0.01) | ||||
| p = 0.09 | |||||
| Education: at least HS | -0.18 (-0.33, -0.03) | ||||
| p = 0.03 | |||||
| Constant | 0.01 (-0.45, 0.48) | 0.01 (-0.38, 0.40) | 0.01 (-0.44, 0.46) | 0.02 (-0.37, 0.42) | 0.09 (-0.26, 0.45) |
| p = 0.96 | p = 0.96 | p = 0.96 | p = 0.92 | p = 0.61 | |
| Observations | 334 | 318 | 301 | 297 | 293 |
| Log Likelihood | -421.69 | -392.09 | -369.17 | -361.22 | -357.15 |
| Akaike Inf. Crit. | 853.38 | 796.18 | 750.33 | 738.44 | 736.29 |
| Bayesian Inf. Crit. | 872.44 | 818.75 | 772.58 | 767.99 | 776.77 |
rsq_table_fun(list(r11_spev, r12_spev, r13_spev, r14_spev, r15_spev))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.00 | 0.08 | 0.06 | 0.11 | 0.14 |
| Conditional | 0.39 | 0.41 | 0.46 | 0.45 | 0.45 |
d3_abs_omit <- d3_byq %>%
select(subj, ctry, question, response) %>%
filter(question %in% c("exwl_01", "exwl_02", "exwl_03", "exwl_04", "exwl_05", "exwl_06",
"exwl_07", "exwl_08", "exwl_09", "exwl_10", "exwl_11", "exwl_12",
"exwl_13", "exwl_14", "exwl_15", "exwl_16", "exwl_17", "exwl_18",
"exwl_19", "exwl_20", "exwl_21", "exwl_22", "exwl_23", "exwl_24",
"exwl_25", "exwl_26", "exwl_27", "exwl_28", "exwl_29", "exwl_30",
"exwl_31", "exwl_32", "exwl_33", "exwl_34")) %>%
filter(question != "exwl_14", question != "exwl_31") %>%
group_by(subj, ctry) %>%
summarise(Absorption = mean(response, na.rm = T)) %>%
ungroup() %>%
group_by(ctry) %>%
mutate(Absorption = scale(Absorption)) %>%
ungroup() %>%
distinct(subj, Absorption) %>%
rename(subject_id = subj) %>%
right_join(d3_fortab %>% select(-Absorption)) %>%
filter(subject_id %in% d3_fortab$subject_id)
`summarise()` has grouped output by 'subj'. You can override using the `.groups` argument.
Joining, by = "subject_id"
r03_spev <- lm(`Spiritual Events` ~ `Absorption`,
data = d3_abs_omit)
r04_spev <- lm(`Spiritual Events` ~ Country * `Absorption`,
data = d3_abs_omit)
r05_spev <- lm(`Spiritual Events` ~ Country * `Absorption`
+ Gender + Age,
data = d3_abs_omit)
r03_dse <- lm(`Daily Spiritual Experiences` ~ `Absorption`,
data = d3_abs_omit)
r04_dse <- lm(`Daily Spiritual Experiences` ~ Country * `Absorption`,
data = d3_abs_omit)
r05_dse <- lm(`Daily Spiritual Experiences` ~ Country * `Absorption`
+ Gender + Age,
data = d3_abs_omit)
table_s32 <- stargazer(r03_spev, r04_spev, r05_spev, r03_dse, r04_dse, r05_dse,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32),
file = "./stargazer_tables/table_s32.html")
htmltools::includeHTML("./stargazer_tables/table_s32.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Absorption | 0.36 (0.28, 0.44) | 0.36 (0.30, 0.42) | 0.36 (0.30, 0.42) | 0.22 (0.14, 0.31) | 0.22 (0.16, 0.28) | 0.22 (0.16, 0.28) |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.0000004 | p = 0.00 | p = 0.00 | |
| Country: Gh. | 0.89 (0.76, 1.01) | 0.90 (0.77, 1.02) | 0.87 (0.75, 0.99) | 0.89 (0.77, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.62, -0.39) | -0.49 (-0.61, -0.36) | -0.18 (-0.29, -0.07) | -0.17 (-0.29, -0.05) | ||
| p = 0.00 | p = 0.00 | p = 0.002 | p = 0.005 | |||
| Country: Ch. | -0.67 (-0.79, -0.55) | -0.67 (-0.80, -0.55) | -1.13 (-1.25, -1.02) | -1.14 (-1.25, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.47, 0.71) | 0.53 (0.39, 0.67) | 0.66 (0.54, 0.77) | 0.58 (0.45, 0.72) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.02 (-0.09, 0.04) | -0.06 (-0.12, 0.001) | ||||
| p = 0.50 | p = 0.06 | |||||
| Age | 0.06 (-0.01, 0.14) | 0.09 (0.02, 0.16) | ||||
| p = 0.10 | p = 0.02 | |||||
| Country: Gh. × Absorption | 0.23 (0.11, 0.36) | 0.23 (0.11, 0.36) | 0.01 (-0.11, 0.13) | 0.005 (-0.11, 0.12) | ||
| p = 0.0003 | p = 0.0003 | p = 0.92 | p = 0.94 | |||
| Country: Th. × Absorption | -0.16 (-0.27, -0.04) | -0.16 (-0.28, -0.04) | 0.08 (-0.03, 0.20) | 0.08 (-0.04, 0.19) | ||
| p = 0.01 | p = 0.01 | p = 0.16 | p = 0.19 | |||
| Country: Ch. × Absorption | -0.13 (-0.25, -0.01) | -0.12 (-0.24, -0.0004) | -0.03 (-0.14, 0.09) | -0.02 (-0.14, 0.10) | ||
| p = 0.04 | p = 0.05 | p = 0.65 | p = 0.73 | |||
| Country: Va. × Absorption | 0.06 (-0.06, 0.18) | 0.05 (-0.07, 0.17) | -0.09 (-0.21, 0.02) | -0.11 (-0.23, 0.01) | ||
| p = 0.34 | p = 0.43 | p = 0.12 | p = 0.08 | |||
| Constant | 0.00 (-0.08, 0.08) | 0.03 (-0.03, 0.09) | 0.02 (-0.04, 0.08) | 0.00 (-0.08, 0.08) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.41 | p = 0.47 | p = 1.00 | p = 0.50 | p = 0.71 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.13 | 0.52 | 0.53 | 0.05 | 0.55 | 0.56 |
| Adjusted R2 | 0.13 | 0.52 | 0.52 | 0.05 | 0.54 | 0.55 |
| Residual Std. Error | 0.94 (df = 517) | 0.70 (df = 509) | 0.70 (df = 501) | 0.98 (df = 517) | 0.67 (df = 509) | 0.67 (df = 501) |
| F Statistic | 75.27*** (df = 1; 517) | 62.17*** (df = 9; 509) | 50.68*** (df = 11; 501) | 26.75*** (df = 1; 517) | 69.85*** (df = 9; 509) | 58.40*** (df = 11; 501) |
r06_spev <- lmer(`Spiritual Events` ~ 1
+ (1 | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d3_abs_omit)
r07_spev <- lmer(`Spiritual Events` ~ `Absorption`
# + (1 + `Absorption` | Country), # perfectly correlated ranfx
+ (1 | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d3_abs_omit)
r08_spev <- lmer(`Spiritual Events` ~ `Absorption`
+ Gender + Age
# + (1 + `Absorption` + Gender + Age | Country), # perfectly correlated ranfx
# + (1 + `Absorption` | Country), # perfectly correlated ranfx
+ (1 | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d3_abs_omit)
r06_dse <- lmer(`Daily Spiritual Experiences` ~ 1
+ (1 | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d3_abs_omit)
r07_dse <- lmer(`Daily Spiritual Experiences` ~ `Absorption`
# + (1 + `Absorption` | Country), # perfectly correlated ranfx
+ (1 | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d3_abs_omit)
r08_dse <- lmer(`Daily Spiritual Experiences` ~ `Absorption`
+ Gender + Age
# + (1 + `Absorption` + Gender + Age | Country),
# + (1 + `Absorption` | Country),
+ (1 | Country), # use this for comparsion with spev
control = lmerControl(optimizer = "bobyqa"),
data = d3_abs_omit)
table_s33 <- stargazer(r06_spev, r07_spev, r08_spev, r06_dse, r07_dse, r08_dse,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 0800,
omit.table.layout = "n",
order = c("^`Absorption`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s33),
file = "./stargazer_tables/table_s33.html")
htmltools::includeHTML("./stargazer_tables/table_s33.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Absorption | 0.36 (0.30, 0.42) | 0.36 (0.29, 0.42) | 0.22 (0.16, 0.28) | 0.22 (0.16, 0.28) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.02 (-0.09, 0.05) | -0.07 (-0.13, -0.004) | ||||
| p = 0.55 | p = 0.04 | |||||
| Age | 0.07 (-0.003, 0.15) | 0.08 (0.01, 0.15) | ||||
| p = 0.07 | p = 0.03 | |||||
| Constant | 0.03 (-0.58, 0.63) | 0.03 (-0.58, 0.63) | 0.02 (-0.57, 0.62) | 0.02 (-0.68, 0.72) | 0.02 (-0.68, 0.72) | 0.01 (-0.68, 0.70) |
| p = 0.94 | p = 0.94 | p = 0.95 | p = 0.96 | p = 0.96 | p = 0.98 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| Log Likelihood | -626.20 | -570.08 | -567.78 | -570.44 | -546.42 | -541.27 |
| Akaike Inf. Crit. | 1,258.40 | 1,148.16 | 1,147.56 | 1,146.88 | 1,100.84 | 1,094.54 |
| Bayesian Inf. Crit. | 1,271.15 | 1,165.16 | 1,173.00 | 1,159.63 | 1,117.85 | 1,119.98 |
rsq_table_fun(list(r06_spev, r07_spev, r08_spev, r06_dse, r07_dse, r08_dse))
| R-squared Type | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Marginal | 0.00 | 0.12 | 0.12 | 0.00 | 0.04 | 0.05 |
| Conditional | 0.43 | 0.55 | 0.54 | 0.56 | 0.60 | 0.60 |
r09_us_spev <- lm(`Spiritual Events` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "US") %>%
mutate_at(vars(`Spiritual Events`, `Absorption`),
~ scale(.)))
r09_gh_spev <- lm(`Spiritual Events` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "Ghana") %>%
mutate_at(vars(`Spiritual Events`, `Absorption`),
~ scale(.)))
r09_th_spev <- lm(`Spiritual Events` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "Thailand") %>%
mutate_at(vars(`Spiritual Events`, `Absorption`),
~ scale(.)))
r09_ch_spev <- lm(`Spiritual Events` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "China") %>%
mutate_at(vars(`Spiritual Events`, `Absorption`),
~ scale(.)))
r09_vt_spev <- lm(`Spiritual Events` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "Vanuatu") %>%
mutate_at(vars(`Spiritual Events`, `Absorption`),
~ scale(.)))
table_s34 <- stargazer(r09_us_spev, r09_gh_spev, r09_th_spev, r09_ch_spev, r09_vt_spev,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Absorption`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s34),
file = "./stargazer_tables/table_s34.html")
htmltools::includeHTML("./stargazer_tables/table_s34.html")
| Spiritual Events | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Absorption | 0.39 (0.21, 0.57) | 0.56 (0.40, 0.73) | 0.43 (0.27, 0.60) | 0.48 (0.32, 0.65) | 0.48 (0.31, 0.65) |
| p = 0.00004 | p = 0.00 | p = 0.000002 | p = 0.0000002 | p = 0.0000005 | |
| Constant | -0.00 (-0.18, 0.18) | -0.00 (-0.17, 0.17) | 0.00 (-0.17, 0.17) | -0.00 (-0.17, 0.17) | 0.00 (-0.17, 0.17) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 106 | 97 | 112 | 104 | 100 |
| R2 | 0.15 | 0.32 | 0.19 | 0.24 | 0.23 |
| Adjusted R2 | 0.14 | 0.31 | 0.18 | 0.23 | 0.22 |
| Residual Std. Error | 0.93 (df = 104) | 0.83 (df = 95) | 0.91 (df = 110) | 0.88 (df = 102) | 0.88 (df = 98) |
| F Statistic | 18.57*** (df = 1; 104) | 43.73*** (df = 1; 95) | 25.50*** (df = 1; 110) | 31.36*** (df = 1; 102) | 29.24*** (df = 1; 98) |
r09_us_dse <- lm(`Daily Spiritual Experiences` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "US") %>%
mutate_at(vars(`Daily Spiritual Experiences`, `Absorption`),
~ scale(.)))
r09_gh_dse <- lm(`Daily Spiritual Experiences` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "Ghana") %>%
mutate_at(vars(`Daily Spiritual Experiences`, `Absorption`),
~ scale(.)))
r09_th_dse <- lm(`Daily Spiritual Experiences` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "Thailand") %>%
mutate_at(vars(`Daily Spiritual Experiences`, `Absorption`),
~ scale(.)))
r09_ch_dse <- lm(`Daily Spiritual Experiences` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "China") %>%
mutate_at(vars(`Daily Spiritual Experiences`, `Absorption`),
~ scale(.)))
r09_vt_dse <- lm(`Daily Spiritual Experiences` ~ `Absorption`,
data = d3_abs_omit %>%
filter(Country == "Vanuatu") %>%
mutate_at(vars(`Daily Spiritual Experiences`, `Absorption`),
~ scale(.)))
table_s35 <- stargazer(r09_us_dse, r09_gh_dse, r09_th_dse, r09_ch_dse, r09_vt_dse,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Absorption`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s35),
file = "./stargazer_tables/table_s35.html")
htmltools::includeHTML("./stargazer_tables/table_s35.html")
| Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Absorption | 0.24 (0.05, 0.43) | 0.35 (0.16, 0.53) | 0.54 (0.38, 0.70) | 0.39 (0.21, 0.57) | 0.20 (0.004, 0.39) |
| p = 0.02 | p = 0.001 | p = 0.00 | p = 0.00005 | p = 0.05 | |
| Constant | 0.00 (-0.19, 0.19) | 0.00 (-0.19, 0.19) | -0.00 (-0.16, 0.16) | 0.00 (-0.18, 0.18) | -0.00 (-0.19, 0.19) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 106 | 97 | 112 | 104 | 100 |
| R2 | 0.06 | 0.12 | 0.29 | 0.15 | 0.04 |
| Adjusted R2 | 0.05 | 0.11 | 0.28 | 0.14 | 0.03 |
| Residual Std. Error | 0.98 (df = 104) | 0.94 (df = 95) | 0.85 (df = 110) | 0.93 (df = 102) | 0.99 (df = 98) |
| F Statistic | 6.36** (df = 1; 104) | 12.87*** (df = 1; 95) | 44.79*** (df = 1; 110) | 18.23*** (df = 1; 102) | 4.00** (df = 1; 98) |
d4_abs_omit <- d4_byq %>%
select(p7_subj, p7_ctry, contains("_abs_")) %>%
select(-ends_with("cat"), -ends_with("total"), -contains("_check")) %>%
select(-p7_abs_sense.presc, -p7_abs_not.physical) %>%
gather(question, response, -p7_subj, -p7_ctry) %>%
group_by(p7_subj, p7_ctry) %>%
summarise(Absorption = mean(response, na.rm = T)) %>%
ungroup() %>%
group_by(p7_ctry) %>%
mutate(Absorption = scale(Absorption)) %>%
ungroup() %>%
distinct(p7_subj, Absorption) %>%
rename(subject_id = p7_subj) %>%
right_join(d4_fortab %>% select(-Absorption)) %>%
filter(subject_id %in% d4_fortab$subject_id)
`summarise()` has grouped output by 'p7_subj'. You can override using the `.groups` argument.
Joining, by = "subject_id"
# longform dataframe
d4_fortab_long_spirit <- d4_abs_omit %>%
gather(Scale, Score,
c(`Spiritual Events`, `Daily Spiritual Experience`)) %>%
mutate(Scale = factor(Scale))
# set contrasts
contrasts(d4_fortab_long_spirit$Country) <- cbind(": Gh." = c(-1, 1, 0, 0, 0),
": Th." = c(-1, 0, 1, 0, 0),
": Ch." = c(-1, 0, 0, 1, 0),
": Va." = c(-1, 0, 0, 0, 1))
contrasts(d4_fortab_long_spirit$Gender) <- cbind(": male" = c(-1, 1))
contrasts(d4_fortab_long_spirit$Scale) <- cbind(": Spiritual Events" = c(-1, 1))
r03_spirit <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r04_spirit <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r05_spirit <- lmer(Score ~ Scale * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r06_spirit <- lmer(Score ~ Scale * Country * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r07_spirit <- lmer(Score ~ Scale * Country * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r08_spirit <- lmer(Score ~ Scale * Country * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r09_spirit <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r10_spirit <- lmer(Score ~ Scale * Country * `Porosity Scale` * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r11_spirit <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * Absorption
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r12_spirit <- lmer(Score ~ Scale * Country * `Porosity Scale` * Absorption
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
table_s40 <- stargazer(r03_spirit, #r04_spirit,
r05_spirit, r06_spirit, #r07_spirit,
r08_spirit, r09_spirit, #r10_spirit,
r11_spirit, #r12_spirit,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^Absorption$",
"^`Porosity Vignettes`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40),
file = "./stargazer_tables/table_s40.html")
htmltools::includeHTML("./stargazer_tables/table_s40.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Porosity Vignettes | 0.53 (0.47, 0.60) | 0.27 (0.20, 0.33) | 0.23 (0.16, 0.29) | 0.23 (0.16, 0.30) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.20 (0.12, 0.28) | 0.20 (0.14, 0.26) | 0.18 (0.11, 0.24) | 0.17 (0.11, 0.24) | ||
| p = 0.0000004 | p = 0.00 | p = 0.0000004 | p = 0.000001 | |||
| Porosity Vignettes × Absorption | -0.01 (-0.07, 0.06) | 0.003 (-0.07, 0.07) | ||||
| p = 0.87 | p = 0.94 | |||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.02 (-0.06, 0.02) | -0.001 (-0.03, 0.03) | -0.02 (-0.06, 0.02) | -0.02 (-0.06, 0.03) |
| p = 0.94 | p = 0.94 | p = 0.38 | p = 0.98 | p = 0.42 | p = 0.43 | |
| Country: Gh. | 0.69 (0.56, 0.82) | 0.83 (0.72, 0.94) | 0.73 (0.60, 0.86) | 0.71 (0.58, 0.84) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.29 (-0.40, -0.17) | -0.29 (-0.39, -0.18) | -0.32 (-0.43, -0.20) | -0.32 (-0.43, -0.20) | ||
| p = 0.000001 | p = 0.0000002 | p = 0.00000004 | p = 0.0000002 | |||
| Country: Ch. | -0.68 (-0.83, -0.52) | -0.86 (-0.97, -0.75) | -0.70 (-0.85, -0.55) | -0.67 (-0.83, -0.52) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.50 (0.36, 0.65) | 0.62 (0.51, 0.74) | 0.53 (0.38, 0.67) | 0.49 (0.34, 0.65) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Scale: Spiritual Events × Country: Gh. | -0.06 (-0.14, 0.02) | -0.02 (-0.08, 0.05) | -0.05 (-0.13, 0.03) | -0.05 (-0.13, 0.03) | ||
| p = 0.12 | p = 0.65 | p = 0.22 | p = 0.24 | |||
| Scale: Spiritual Events × Country: Th. | -0.09 (-0.16, -0.02) | -0.12 (-0.18, -0.05) | -0.10 (-0.18, -0.03) | -0.11 (-0.18, -0.03) | ||
| p = 0.02 | p = 0.001 | p = 0.005 | p = 0.01 | |||
| Scale: Spiritual Events × Country: Ch. | 0.16 (0.06, 0.26) | 0.20 (0.13, 0.27) | 0.16 (0.06, 0.26) | 0.16 (0.06, 0.26) | ||
| p = 0.002 | p = 0.00 | p = 0.002 | p = 0.003 | |||
| Scale: Spiritual Events × Country: Va. | -0.13 (-0.22, -0.03) | -0.14 (-0.21, -0.07) | -0.10 (-0.19, -0.01) | -0.10 (-0.20, -0.003) | ||
| p = 0.01 | p = 0.0002 | p = 0.04 | p = 0.05 | |||
| Scale: Spiritual Events × Porosity Vignettes | 0.01 (-0.03, 0.04) | 0.04 (-0.003, 0.08) | 0.03 (-0.01, 0.07) | 0.03 (-0.01, 0.08) | ||
| p = 0.75 | p = 0.07 | p = 0.20 | p = 0.17 | |||
| Gender: male | -0.02 (-0.07, 0.04) | |||||
| p = 0.58 | ||||||
| Age | 0.06 (-0.01, 0.12) | |||||
| p = 0.08 | ||||||
| Scale: Spiritual Events × Absorption | 0.04 (0.01, 0.08) | 0.04 (0.01, 0.08) | 0.05 (0.01, 0.09) | 0.05 (0.004, 0.09) | ||
| p = 0.02 | p = 0.02 | p = 0.03 | p = 0.04 | |||
| Country: Gh. × Porosity Vignettes | -0.11 (-0.23, 0.002) | -0.11 (-0.23, 0.01) | -0.12 (-0.23, 0.002) | |||
| p = 0.06 | p = 0.07 | p = 0.06 | ||||
| Country: Th. × Porosity Vignettes | -0.04 (-0.17, 0.08) | -0.07 (-0.19, 0.06) | -0.08 (-0.21, 0.04) | |||
| p = 0.49 | p = 0.28 | p = 0.20 | ||||
| Country: Ch. × Porosity Vignettes | 0.07 (-0.10, 0.23) | 0.08 (-0.08, 0.25) | 0.06 (-0.10, 0.23) | |||
| p = 0.45 | p = 0.33 | p = 0.45 | ||||
| Country: Va. × Porosity Vignettes | -0.15 (-0.30, -0.0001) | -0.14 (-0.30, 0.01) | -0.14 (-0.30, 0.01) | |||
| p = 0.05 | p = 0.07 | p = 0.08 | ||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.07 (-0.003, 0.14) | 0.07 (-0.002, 0.15) | 0.07 (-0.01, 0.15) | |||
| p = 0.06 | p = 0.06 | p = 0.08 | ||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.01 (-0.09, 0.07) | 0.003 (-0.08, 0.08) | 0.0004 (-0.08, 0.08) | |||
| p = 0.85 | p = 0.94 | p = 1.00 | ||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.12 (-0.22, -0.01) | -0.11 (-0.22, -0.01) | -0.12 (-0.22, -0.01) | |||
| p = 0.04 | p = 0.04 | p = 0.04 | ||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.03 (-0.13, 0.07) | -0.04 (-0.14, 0.05) | -0.05 (-0.15, 0.06) | |||
| p = 0.54 | p = 0.37 | p = 0.38 | ||||
| Country: Gh. × Absorption | -0.04 (-0.16, 0.07) | -0.01 (-0.13, 0.11) | -0.001 (-0.12, 0.12) | |||
| p = 0.45 | p = 0.91 | p = 0.99 | ||||
| Country: Th. × Absorption | 0.03 (-0.07, 0.14) | 0.03 (-0.09, 0.14) | 0.03 (-0.08, 0.14) | |||
| p = 0.54 | p = 0.64 | p = 0.61 | ||||
| Country: Ch. × Absorption | -0.03 (-0.15, 0.08) | 0.04 (-0.13, 0.21) | 0.04 (-0.13, 0.21) | |||
| p = 0.57 | p = 0.62 | p = 0.64 | ||||
| Country: Va. × Absorption | -0.07 (-0.18, 0.05) | -0.01 (-0.16, 0.13) | -0.01 (-0.16, 0.14) | |||
| p = 0.26 | p = 0.86 | p = 0.90 | ||||
| Scale: Spiritual Events × Country: Gh. × Absorption | 0.01 (-0.06, 0.08) | -0.01 (-0.08, 0.07) | -0.01 (-0.09, 0.07) | |||
| p = 0.80 | p = 0.88 | p = 0.88 | ||||
| Scale: Spiritual Events × Country: Th. × Absorption | -0.04 (-0.11, 0.02) | -0.05 (-0.12, 0.02) | -0.05 (-0.12, 0.02) | |||
| p = 0.20 | p = 0.18 | p = 0.19 | ||||
| Scale: Spiritual Events × Country: Ch. × Absorption | -0.01 (-0.08, 0.06) | -0.02 (-0.13, 0.09) | -0.02 (-0.14, 0.09) | |||
| p = 0.86 | p = 0.68 | p = 0.68 | ||||
| Scale: Spiritual Events × Country: Va. × Absorption | 0.01 (-0.07, 0.08) | 0.08 (-0.02, 0.17) | 0.07 (-0.03, 0.18) | |||
| p = 0.88 | p = 0.11 | p = 0.15 | ||||
| Scale: Spiritual Events × Porosity Vignettes × Absorption | -0.01 (-0.06, 0.03) | -0.01 (-0.06, 0.03) | ||||
| p = 0.56 | p = 0.65 | |||||
| Country: Gh. × Porosity Vignettes × Absorption | -0.10 (-0.21, 0.01) | -0.10 (-0.22, 0.01) | ||||
| p = 0.09 | p = 0.08 | |||||
| Country: Th. × Porosity Vignettes × Absorption | 0.06 (-0.06, 0.19) | 0.05 (-0.07, 0.18) | ||||
| p = 0.33 | p = 0.42 | |||||
| Country: Ch. × Porosity Vignettes × Absorption | 0.09 (-0.08, 0.27) | 0.07 (-0.10, 0.25) | ||||
| p = 0.30 | p = 0.42 | |||||
| Country: Va. × Porosity Vignettes × Absorption | -0.05 (-0.19, 0.09) | -0.06 (-0.21, 0.08) | ||||
| p = 0.49 | p = 0.40 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes × Absorption | -0.02 (-0.10, 0.05) | -0.03 (-0.10, 0.05) | ||||
| p = 0.54 | p = 0.50 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes × Absorption | 0.07 (-0.01, 0.15) | 0.07 (-0.01, 0.15) | ||||
| p = 0.08 | p = 0.09 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes × Absorption | -0.01 (-0.12, 0.11) | -0.01 (-0.13, 0.11) | ||||
| p = 0.90 | p = 0.88 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes × Absorption | -0.10 (-0.19, -0.01) | -0.10 (-0.19, -0.00002) | ||||
| p = 0.04 | p = 0.05 | |||||
| Constant | -0.001 (-0.07, 0.06) | -0.001 (-0.08, 0.08) | 0.06 (-0.002, 0.13) | 0.02 (-0.04, 0.07) | 0.07 (0.002, 0.13) | 0.06 (-0.01, 0.13) |
| p = 0.97 | p = 0.98 | p = 0.06 | p = 0.56 | p = 0.05 | p = 0.10 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 1,008 | 978 |
| Log Likelihood | -1,186.34 | -1,275.26 | -1,082.26 | -1,113.46 | -1,105.26 | -1,083.77 |
| Akaike Inf. Crit. | 2,384.67 | 2,562.52 | 2,208.53 | 2,270.93 | 2,294.51 | 2,255.54 |
| Bayesian Inf. Crit. | 2,414.16 | 2,592.01 | 2,316.67 | 2,379.08 | 2,500.97 | 2,470.50 |
rsq_table_fun(list(r03_spirit, #r04_spirit,
r05_spirit, r06_spirit, #r07_spirit,
r08_spirit, r09_spirit, #r10_spirit,
r11_spirit #, r12_spirit
))
| R-squared Type | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Marginal | 0.28 | 0.04 | 0.49 | 0.45 | 0.51 | 0.51 |
| Conditional | 0.67 | 0.67 | 0.71 | 0.70 | 0.71 | 0.71 |
table_s41 <- stargazer(#r03_spirit,
r04_spirit, r05_spirit, #r06_spirit,
r07_spirit, r08_spirit, #r09_spirit,
r10_spirit, #r11_spirit,
r12_spirit,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Scale`$",
"^Absorption$",
"^`Porosity Scale`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s41),
file = "./stargazer_tables/table_s41.html")
htmltools::includeHTML("./stargazer_tables/table_s41.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Porosity Scale | 0.62 (0.56, 0.68) | 0.36 (0.29, 0.44) | 0.32 (0.25, 0.39) | 0.33 (0.25, 0.40) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.20 (0.12, 0.28) | 0.20 (0.14, 0.26) | 0.15 (0.07, 0.22) | 0.14 (0.07, 0.22) | ||
| p = 0.0000004 | p = 0.00 | p = 0.0001 | p = 0.0002 | |||
| Porosity Scale × Absorption | 0.02 (-0.05, 0.09) | 0.02 (-0.04, 0.09) | ||||
| p = 0.57 | p = 0.49 | |||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.002 (-0.05, 0.05) | -0.001 (-0.03, 0.03) | -0.01 (-0.06, 0.04) | -0.004 (-0.06, 0.05) |
| p = 0.94 | p = 0.94 | p = 0.94 | p = 0.98 | p = 0.81 | p = 0.88 | |
| Country: Gh. | 0.62 (0.49, 0.75) | 0.83 (0.72, 0.94) | 0.65 (0.52, 0.78) | 0.62 (0.49, 0.76) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.24 (-0.36, -0.13) | -0.29 (-0.39, -0.18) | -0.26 (-0.37, -0.14) | -0.25 (-0.37, -0.12) | ||
| p = 0.00004 | p = 0.0000002 | p = 0.00002 | p = 0.0001 | |||
| Country: Ch. | -0.57 (-0.73, -0.41) | -0.86 (-0.97, -0.75) | -0.63 (-0.80, -0.46) | -0.61 (-0.78, -0.44) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.38 (0.19, 0.57) | 0.62 (0.51, 0.74) | 0.42 (0.22, 0.61) | 0.38 (0.18, 0.58) | ||
| p = 0.0002 | p = 0.00 | p = 0.00004 | p = 0.0003 | |||
| Scale: Spiritual Events × Country: Gh. | -0.07 (-0.16, 0.01) | -0.02 (-0.08, 0.05) | -0.05 (-0.14, 0.03) | -0.06 (-0.14, 0.03) | ||
| p = 0.10 | p = 0.65 | p = 0.24 | p = 0.23 | |||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.20, -0.04) | -0.12 (-0.18, -0.05) | -0.13 (-0.21, -0.05) | -0.13 (-0.21, -0.05) | ||
| p = 0.003 | p = 0.001 | p = 0.002 | p = 0.002 | |||
| Scale: Spiritual Events × Country: Ch. | 0.13 (0.02, 0.23) | 0.20 (0.13, 0.27) | 0.09 (-0.02, 0.21) | 0.09 (-0.02, 0.21) | ||
| p = 0.02 | p = 0.00 | p = 0.11 | p = 0.13 | |||
| Scale: Spiritual Events × Country: Va. | -0.02 (-0.15, 0.10) | -0.14 (-0.21, -0.07) | 0.01 (-0.13, 0.14) | 0.01 (-0.12, 0.15) | ||
| p = 0.72 | p = 0.0002 | p = 0.94 | p = 0.87 | |||
| Scale: Spiritual Events × Porosity Scale | -0.05 (-0.08, -0.01) | -0.01 (-0.06, 0.03) | -0.03 (-0.08, 0.02) | -0.03 (-0.08, 0.02) | ||
| p = 0.01 | p = 0.57 | p = 0.21 | p = 0.20 | |||
| Gender: male | 0.02 (-0.04, 0.08) | |||||
| p = 0.51 | ||||||
| Age | 0.05 (-0.01, 0.11) | |||||
| p = 0.13 | ||||||
| Scale: Spiritual Events × Absorption | 0.04 (0.01, 0.08) | 0.04 (0.01, 0.08) | 0.06 (0.01, 0.11) | 0.06 (0.01, 0.11) | ||
| p = 0.02 | p = 0.02 | p = 0.02 | p = 0.02 | |||
| Country: Gh. × Porosity Scale | -0.10 (-0.22, 0.03) | -0.08 (-0.20, 0.05) | -0.08 (-0.21, 0.05) | |||
| p = 0.14 | p = 0.25 | p = 0.22 | ||||
| Country: Th. × Porosity Scale | -0.02 (-0.16, 0.11) | -0.03 (-0.16, 0.10) | -0.04 (-0.17, 0.10) | |||
| p = 0.73 | p = 0.64 | p = 0.58 | ||||
| Country: Ch. × Porosity Scale | 0.06 (-0.09, 0.21) | 0.04 (-0.12, 0.20) | 0.03 (-0.13, 0.19) | |||
| p = 0.43 | p = 0.59 | p = 0.73 | ||||
| Country: Va. × Porosity Scale | -0.17 (-0.34, 0.01) | -0.16 (-0.34, 0.02) | -0.15 (-0.33, 0.03) | |||
| p = 0.07 | p = 0.09 | p = 0.11 | ||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.12 (0.03, 0.20) | 0.13 (0.04, 0.22) | 0.13 (0.04, 0.22) | |||
| p = 0.01 | p = 0.004 | p = 0.004 | ||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | -0.001 (-0.09, 0.09) | 0.02 (-0.07, 0.11) | 0.02 (-0.07, 0.11) | |||
| p = 0.98 | p = 0.70 | p = 0.72 | ||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.07 (-0.17, 0.03) | -0.09 (-0.20, 0.02) | -0.09 (-0.20, 0.02) | |||
| p = 0.17 | p = 0.10 | p = 0.11 | ||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.11 (-0.22, 0.01) | -0.11 (-0.23, 0.01) | -0.12 (-0.24, 0.003) | |||
| p = 0.08 | p = 0.07 | p = 0.06 | ||||
| Country: Gh. × Absorption | -0.04 (-0.16, 0.07) | -0.01 (-0.13, 0.11) | -0.01 (-0.13, 0.12) | |||
| p = 0.45 | p = 0.87 | p = 0.93 | ||||
| Country: Th. × Absorption | 0.03 (-0.07, 0.14) | 0.05 (-0.07, 0.16) | 0.05 (-0.06, 0.17) | |||
| p = 0.54 | p = 0.43 | p = 0.39 | ||||
| Country: Ch. × Absorption | -0.03 (-0.15, 0.08) | 0.01 (-0.16, 0.18) | 0.01 (-0.16, 0.18) | |||
| p = 0.57 | p = 0.88 | p = 0.92 | ||||
| Country: Va. × Absorption | -0.07 (-0.18, 0.05) | -0.09 (-0.28, 0.10) | -0.10 (-0.29, 0.10) | |||
| p = 0.26 | p = 0.38 | p = 0.33 | ||||
| Scale: Spiritual Events × Country: Gh. × Absorption | 0.01 (-0.06, 0.08) | -0.004 (-0.09, 0.08) | -0.004 (-0.09, 0.08) | |||
| p = 0.80 | p = 0.93 | p = 0.93 | ||||
| Scale: Spiritual Events × Country: Th. × Absorption | -0.04 (-0.11, 0.02) | -0.05 (-0.12, 0.03) | -0.05 (-0.12, 0.03) | |||
| p = 0.20 | p = 0.25 | p = 0.26 | ||||
| Scale: Spiritual Events × Country: Ch. × Absorption | -0.01 (-0.08, 0.06) | 0.03 (-0.08, 0.15) | 0.03 (-0.08, 0.15) | |||
| p = 0.86 | p = 0.59 | p = 0.59 | ||||
| Scale: Spiritual Events × Country: Va. × Absorption | 0.01 (-0.07, 0.08) | 0.004 (-0.13, 0.13) | -0.005 (-0.14, 0.13) | |||
| p = 0.88 | p = 0.96 | p = 0.95 | ||||
| Scale: Spiritual Events × Porosity Scale × Absorption | 0.01 (-0.03, 0.06) | 0.02 (-0.03, 0.06) | ||||
| p = 0.54 | p = 0.49 | |||||
| Country: Gh. × Porosity Scale × Absorption | -0.09 (-0.21, 0.03) | -0.09 (-0.21, 0.03) | ||||
| p = 0.16 | p = 0.16 | |||||
| Country: Th. × Porosity Scale × Absorption | 0.02 (-0.11, 0.15) | 0.02 (-0.11, 0.15) | ||||
| p = 0.80 | p = 0.79 | |||||
| Country: Ch. × Porosity Scale × Absorption | 0.06 (-0.09, 0.21) | 0.04 (-0.11, 0.19) | ||||
| p = 0.44 | p = 0.60 | |||||
| Country: Va. × Porosity Scale × Absorption | 0.04 (-0.14, 0.21) | 0.04 (-0.13, 0.21) | ||||
| p = 0.69 | p = 0.66 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale × Absorption | -0.08 (-0.16, 0.01) | -0.08 (-0.16, 0.004) | ||||
| p = 0.07 | p = 0.07 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale × Absorption | 0.07 (-0.02, 0.15) | 0.07 (-0.02, 0.15) | ||||
| p = 0.15 | p = 0.15 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale × Absorption | 0.02 (-0.08, 0.12) | 0.02 (-0.08, 0.12) | ||||
| p = 0.67 | p = 0.72 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale × Absorption | -0.01 (-0.13, 0.10) | -0.01 (-0.13, 0.11) | ||||
| p = 0.82 | p = 0.85 | |||||
| Constant | -0.001 (-0.06, 0.06) | -0.001 (-0.08, 0.08) | 0.07 (-0.001, 0.15) | 0.02 (-0.04, 0.07) | 0.06 (-0.01, 0.14) | 0.07 (-0.01, 0.14) |
| p = 0.97 | p = 0.98 | p = 0.06 | p = 0.56 | p = 0.10 | p = 0.10 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 1,008 | 978 |
| Log Likelihood | -1,133.48 | -1,275.26 | -1,066.20 | -1,113.46 | -1,089.04 | -1,069.60 |
| Akaike Inf. Crit. | 2,278.96 | 2,562.52 | 2,176.40 | 2,270.93 | 2,262.09 | 2,227.21 |
| Bayesian Inf. Crit. | 2,308.46 | 2,592.01 | 2,284.55 | 2,379.08 | 2,468.55 | 2,442.17 |
rsq_table_fun(list(#r03_spirit,
r04_spirit, r05_spirit, #r06_spirit,
r07_spirit, r08_spirit, #r09_spirit,
r10_spirit, #r11_spirit,
r12_spirit))
| R-squared Type | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Marginal | 0.38 | 0.04 | 0.51 | 0.45 | 0.53 | 0.53 |
| Conditional | 0.67 | 0.67 | 0.70 | 0.70 | 0.71 | 0.70 |
r13_spirit <- lmer(Score ~ Scale
+ (1 | Country/subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r14_spirit <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | Country/subject_id),
# + (1 + `Porosity Vignettes` | Country), # adding to above, failed to converge
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r15_spirit <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | Country/subject_id),
# + (1 + `Porosity Scale` | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r16_spirit <- lmer(Score ~ Scale * Absorption
+ (1 | Country/subject_id),
# + (1 + Absorption | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r17_spirit <- lmer(Score ~ Scale * `Porosity Vignettes` * Absorption
+ (1 | Country/subject_id),
# + (1 + `Porosity Vignettes` * Absorption | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r18_spirit <- lmer(Score ~ Scale * `Porosity Scale` * Absorption
+ (1 | Country/subject_id),
# + (1 + `Porosity Scale` * Absorption | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r19_spirit <- lmer(Score ~ Scale * `Porosity Vignettes` * Absorption
+ Gender + Age
+ (1 | Country/subject_id),
# + (1 + `Porosity Vignettes` * Absorption + Gender + Age | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
r20_spirit <- lmer(Score ~ Scale * `Porosity Scale` * Absorption
+ Gender + Age
+ (1 | Country/subject_id),
# + (1 + `Porosity Scale` * Absorption + Gender + Age | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit)
table_s42 <- stargazer(r13_spirit, r14_spirit, #r15_spirit,
r16_spirit, r17_spirit, #r18_spirit,
r19_spirit, #r20_spirit,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^Absorption$",
"^`Porosity Vignettes`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s42),
file = "./stargazer_tables/table_s42.html")
htmltools::includeHTML("./stargazer_tables/table_s42.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.29 (0.23, 0.36) | 0.25 (0.19, 0.32) | 0.26 (0.19, 0.32) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.20 (0.15, 0.26) | 0.15 (0.10, 0.20) | 0.15 (0.09, 0.20) | ||
| p = 0.00 | p = 0.0000001 | p = 0.0000002 | |||
| Porosity Vignettes × Absorption | -0.03 (-0.08, 0.03) | -0.02 (-0.07, 0.04) | |||
| p = 0.33 | p = 0.51 | ||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.0004 (-0.04, 0.04) | 0.002 (-0.04, 0.04) |
| p = 0.96 | p = 0.96 | p = 0.97 | p = 0.99 | p = 0.94 | |
| Scale: Spiritual Events × Porosity Vignettes | 0.01 (-0.03, 0.04) | -0.003 (-0.04, 0.03) | -0.0002 (-0.04, 0.04) | ||
| p = 0.74 | p = 0.88 | p = 1.00 | |||
| Gender: male | -0.01 (-0.07, 0.04) | ||||
| p = 0.63 | |||||
| Age | 0.06 (-0.003, 0.13) | ||||
| p = 0.06 | |||||
| Scale: Spiritual Events × Absorption | 0.04 (0.01, 0.08) | 0.04 (0.01, 0.08) | 0.04 (0.003, 0.08) | ||
| p = 0.02 | p = 0.02 | p = 0.04 | |||
| Scale: Spiritual Events × Porosity Vignettes × Absorption | -0.002 (-0.04, 0.03) | -0.002 (-0.04, 0.03) | |||
| p = 0.91 | p = 0.91 | ||||
| Constant | 0.02 (-0.60, 0.63) | 0.01 (-0.46, 0.48) | 0.02 (-0.60, 0.63) | 0.02 (-0.47, 0.51) | 0.01 (-0.45, 0.47) |
| p = 0.96 | p = 0.97 | p = 0.96 | p = 0.95 | p = 0.97 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 |
| Log Likelihood | -1,137.87 | -1,104.88 | -1,116.83 | -1,098.85 | -1,078.25 |
| Akaike Inf. Crit. | 2,285.74 | 2,223.76 | 2,247.67 | 2,219.71 | 2,182.49 |
| Bayesian Inf. Crit. | 2,310.32 | 2,258.17 | 2,282.08 | 2,273.78 | 2,246.00 |
rsq_table_fun(list(r13_spirit, r14_spirit, #r15_spirit,
r16_spirit, r17_spirit, #r18_spirit,
r19_spirit #, r20_spirit
))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.0 | 0.09 | 0.04 | 0.11 | 0.12 |
| Conditional | 0.7 | 0.64 | 0.70 | 0.65 | 0.64 |
table_s43 <- stargazer(r13_spirit, #r14_spirit,
r15_spirit, r16_spirit, #r17_spirit,
r18_spirit, #r19_spirit,
r20_spirit,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Scale`$",
"^Absorption$",
"^`Porosity Scale`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s43),
file = "./stargazer_tables/table_s43.html")
htmltools::includeHTML("./stargazer_tables/table_s43.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Scale | 0.41 (0.34, 0.47) | 0.36 (0.30, 0.43) | 0.37 (0.30, 0.44) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.20 (0.15, 0.26) | 0.13 (0.08, 0.19) | 0.13 (0.08, 0.19) | ||
| p = 0.00 | p = 0.0000005 | p = 0.000002 | |||
| Porosity Scale × Absorption | -0.002 (-0.05, 0.05) | -0.002 (-0.05, 0.05) | |||
| p = 0.94 | p = 0.95 | ||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.004 (-0.04, 0.03) | -0.002 (-0.04, 0.03) |
| p = 0.96 | p = 0.96 | p = 0.97 | p = 0.85 | p = 0.91 | |
| Scale: Spiritual Events × Porosity Scale | -0.05 (-0.08, -0.01) | -0.06 (-0.09, -0.02) | -0.06 (-0.09, -0.02) | ||
| p = 0.02 | p = 0.002 | p = 0.004 | |||
| Gender: male | 0.03 (-0.03, 0.08) | ||||
| p = 0.35 | |||||
| Age | 0.05 (-0.01, 0.11) | ||||
| p = 0.11 | |||||
| Scale: Spiritual Events × Absorption | 0.04 (0.01, 0.08) | 0.05 (0.02, 0.09) | 0.05 (0.01, 0.09) | ||
| p = 0.02 | p = 0.004 | p = 0.01 | |||
| Scale: Spiritual Events × Porosity Scale × Absorption | 0.01 (-0.02, 0.05) | 0.01 (-0.02, 0.05) | |||
| p = 0.41 | p = 0.45 | ||||
| Constant | 0.02 (-0.60, 0.63) | 0.01 (-0.38, 0.39) | 0.02 (-0.60, 0.63) | 0.01 (-0.40, 0.41) | 0.01 (-0.37, 0.39) |
| p = 0.96 | p = 0.98 | p = 0.96 | p = 0.97 | p = 0.95 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 |
| Log Likelihood | -1,137.87 | -1,076.95 | -1,116.83 | -1,071.59 | -1,051.97 |
| Akaike Inf. Crit. | 2,285.74 | 2,167.90 | 2,247.67 | 2,165.18 | 2,129.93 |
| Bayesian Inf. Crit. | 2,310.32 | 2,202.31 | 2,282.08 | 2,219.26 | 2,193.44 |
rsq_table_fun(list(r13_spirit, #r14_spirit,
r15_spirit, r16_spirit, #r17_spirit,
r18_spirit, #r19_spirit
r20_spirit
))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.0 | 0.19 | 0.04 | 0.20 | 0.22 |
| Conditional | 0.7 | 0.62 | 0.70 | 0.63 | 0.62 |
r21_spirit_us <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "US") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
r21_spirit_gh <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Ghana") %>%
mutate_at(vars(Score, ,`Porosity Vignettes`), ~ scale(.)))
r21_spirit_th <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Thailand") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
r21_spirit_ch <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "China") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
r21_spirit_vt <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Vanuatu") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
table_s44 <- stargazer(r21_spirit_us, r21_spirit_gh, r21_spirit_th,
r21_spirit_ch, r21_spirit_vt,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s44),
file = "./stargazer_tables/table_s44.html")
htmltools::includeHTML("./stargazer_tables/table_s44.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.53 (0.38, 0.67) | 0.17 (0.02, 0.33) | 0.28 (0.13, 0.44) | 0.34 (0.19, 0.48) | 0.12 (-0.05, 0.28) |
| p = 0.00 | p = 0.03 | p = 0.0003 | p = 0.00001 | p = 0.18 | |
| Scale: Spiritual Events | 0.07 (-0.01, 0.14) | -0.02 (-0.13, 0.10) | -0.18 (-0.26, -0.09) | 0.33 (0.23, 0.43) | -0.20 (-0.31, -0.08) |
| p = 0.08 | p = 0.77 | p = 0.0001 | p = 0.00 | p = 0.001 | |
| Scale: Spiritual Events × Porosity Vignettes | 0.13 (0.05, 0.20) | 0.13 (0.01, 0.24) | 0.04 (-0.05, 0.13) | -0.08 (-0.17, 0.02) | 0.01 (-0.10, 0.13) |
| p = 0.001 | p = 0.04 | p = 0.36 | p = 0.12 | p = 0.87 | |
| Constant | -0.00 (-0.15, 0.15) | -0.003 (-0.16, 0.15) | -0.00 (-0.15, 0.15) | -0.0001 (-0.14, 0.14) | 0.00 (-0.16, 0.16) |
| p = 1.00 | p = 0.97 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 204 | 199 | 222 | 199 | 184 |
| Log Likelihood | -238.99 | -280.13 | -292.61 | -255.25 | -256.66 |
| Akaike Inf. Crit. | 489.98 | 572.26 | 597.23 | 522.50 | 525.33 |
| Bayesian Inf. Crit. | 509.89 | 592.02 | 617.64 | 542.26 | 544.62 |
rsq_table_fun(list(r21_spirit_us, r21_spirit_gh, r21_spirit_th,
r21_spirit_ch, r21_spirit_vt))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.30 | 0.05 | 0.11 | 0.23 | 0.05 |
| Conditional | 0.71 | 0.32 | 0.56 | 0.53 | 0.38 |
r22_spirit_us <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "US") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_spirit_gh <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Ghana") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_spirit_th <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Thailand") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_spirit_ch <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "China") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_spirit_vt <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Vanuatu") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
table_s45 <- stargazer(r22_spirit_us, r22_spirit_gh, r22_spirit_th,
r22_spirit_ch, r22_spirit_vt,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Scale`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s45),
file = "./stargazer_tables/table_s45.html")
htmltools::includeHTML("./stargazer_tables/table_s45.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Scale | 0.56 (0.41, 0.70) | 0.27 (0.12, 0.42) | 0.40 (0.25, 0.54) | 0.47 (0.34, 0.60) | 0.16 (-0.002, 0.32) |
| p = 0.00 | p = 0.0004 | p = 0.0000001 | p = 0.00 | p = 0.06 | |
| Scale: Spiritual Events | 0.07 (-0.01, 0.15) | -0.02 (-0.13, 0.10) | -0.18 (-0.27, -0.09) | 0.33 (0.23, 0.43) | -0.20 (-0.31, -0.08) |
| p = 0.09 | p = 0.77 | p = 0.0001 | p = 0.00 | p = 0.001 | |
| Scale: Spiritual Events × Porosity Scale | 0.04 (-0.03, 0.12) | 0.10 (-0.01, 0.22) | -0.02 (-0.11, 0.07) | -0.09 (-0.19, 0.002) | -0.10 (-0.21, 0.02) |
| p = 0.27 | p = 0.09 | p = 0.70 | p = 0.06 | p = 0.10 | |
| Constant | 0.00 (-0.14, 0.14) | -0.003 (-0.15, 0.15) | -0.00 (-0.14, 0.14) | -0.001 (-0.13, 0.13) | 0.00 (-0.16, 0.16) |
| p = 1.00 | p = 0.97 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 204 | 199 | 222 | 199 | 184 |
| Log Likelihood | -241.07 | -277.32 | -286.41 | -243.43 | -254.39 |
| Akaike Inf. Crit. | 494.14 | 566.64 | 584.81 | 498.86 | 520.79 |
| Bayesian Inf. Crit. | 514.05 | 586.40 | 605.23 | 518.62 | 540.08 |
rsq_table_fun(list(r22_spirit_us, r22_spirit_gh, r22_spirit_th,
r22_spirit_ch, r22_spirit_vt))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.31 | 0.08 | 0.19 | 0.34 | 0.07 |
| Conditional | 0.68 | 0.31 | 0.55 | 0.53 | 0.40 |
r23_spirit_us <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "US") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_spirit_gh <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Ghana") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_spirit_th <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Thailand") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_spirit_ch <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "China") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_spirit_vt <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_spirit %>% filter(Country == "Vanuatu") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
table_s46 <- stargazer(r23_spirit_us, r23_spirit_gh, r23_spirit_th,
r23_spirit_ch, r23_spirit_vt,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s46),
file = "./stargazer_tables/table_s46.html")
htmltools::includeHTML("./stargazer_tables/table_s46.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Absorption | 0.30 (0.13, 0.47) | 0.18 (0.03, 0.34) | 0.36 (0.21, 0.50) | 0.28 (0.13, 0.43) | 0.19 (0.03, 0.35) |
| p = 0.0005 | p = 0.03 | p = 0.000003 | p = 0.0003 | p = 0.03 | |
| Scale: Spiritual Events | 0.07 (-0.01, 0.15) | -0.02 (-0.14, 0.10) | -0.18 (-0.27, -0.09) | 0.33 (0.24, 0.43) | -0.20 (-0.31, -0.08) |
| p = 0.09 | p = 0.77 | p = 0.0001 | p = 0.00 | p = 0.001 | |
| Scale: Spiritual Events × Absorption | 0.08 (0.001, 0.15) | 0.06 (-0.06, 0.18) | 0.001 (-0.09, 0.09) | 0.06 (-0.03, 0.16) | 0.07 (-0.04, 0.18) |
| p = 0.05 | p = 0.31 | p = 0.99 | p = 0.21 | p = 0.23 | |
| Constant | -0.00 (-0.17, 0.17) | -0.003 (-0.16, 0.15) | -0.00 (-0.15, 0.15) | 0.002 (-0.15, 0.15) | 0.00 (-0.16, 0.16) |
| p = 1.00 | p = 0.97 | p = 1.00 | p = 0.98 | p = 1.00 | |
| Observations | 204 | 199 | 222 | 199 | 184 |
| Log Likelihood | -257.02 | -281.60 | -289.18 | -258.75 | -254.37 |
| Akaike Inf. Crit. | 526.03 | 575.21 | 590.36 | 529.50 | 520.74 |
| Bayesian Inf. Crit. | 545.94 | 594.97 | 610.78 | 549.26 | 540.03 |
rsq_table_fun(list(r23_spirit_us, r23_spirit_gh, r23_spirit_th,
r23_spirit_ch, r23_spirit_vt))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.10 | 0.04 | 0.16 | 0.19 | 0.08 |
| Conditional | 0.69 | 0.29 | 0.55 | 0.52 | 0.39 |
# longform dataframe
d4_fortab_long_secular <- d4_abs_omit %>%
gather(Scale, Score,
c(Hallucinations, Paranormal)) %>%
mutate(Scale = factor(Scale))
# set contrasts
contrasts(d4_fortab_long_secular$Country) <- cbind(": Gh." = c(-1, 1, 0, 0, 0),
": Th." = c(-1, 0, 1, 0, 0),
": Ch." = c(-1, 0, 0, 1, 0),
": Va." = c(-1, 0, 0, 0, 1))
contrasts(d4_fortab_long_secular$Gender) <- cbind(": male" = c(-1, 1))
contrasts(d4_fortab_long_secular$Scale) <- cbind(": Hallucinations" = c(1, -1))
r03_secular <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r04_secular <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r05_secular <- lmer(Score ~ Scale * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r06_secular <- lmer(Score ~ Scale * Country * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r07_secular <- lmer(Score ~ Scale * Country * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r08_secular <- lmer(Score ~ Scale * Country * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r09_secular <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r10_secular <- lmer(Score ~ Scale * Country * `Porosity Scale` * Absorption
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r11_secular <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * Absorption
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r12_secular <- lmer(Score ~ Scale * Country * `Porosity Scale` * Absorption
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
table_s47 <- stargazer(r03_secular, #r04_secular,
r05_secular, r06_secular, #r07_secular,
r08_secular, r09_secular, #r10_secular,
r11_secular, #r12_secular,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^Absorption$",
"^`Porosity Vignettes`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s47),
file = "./stargazer_tables/table_s47.html")
htmltools::includeHTML("./stargazer_tables/table_s47.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Porosity Vignettes | 0.31 (0.24, 0.37) | 0.34 (0.26, 0.41) | 0.26 (0.19, 0.34) | 0.26 (0.19, 0.34) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.34 (0.27, 0.40) | 0.33 (0.27, 0.40) | 0.32 (0.24, 0.39) | 0.30 (0.22, 0.37) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Porosity Vignettes × Absorption | -0.002 (-0.08, 0.07) | 0.01 (-0.06, 0.08) | ||||
| p = 0.96 | p = 0.81 | |||||
| Scale: Hallucinations | 0.00 (-0.05, 0.05) | 0.00 (-0.05, 0.05) | -0.07 (-0.13, -0.01) | 0.002 (-0.05, 0.05) | -0.06 (-0.13, -0.0001) | -0.07 (-0.13, -0.001) |
| p = 1.00 | p = 1.00 | p = 0.03 | p = 0.96 | p = 0.05 | p = 0.05 | |
| Country: Gh. | 0.01 (-0.13, 0.16) | 0.24 (0.12, 0.37) | 0.07 (-0.07, 0.21) | 0.12 (-0.03, 0.26) | ||
| p = 0.85 | p = 0.0002 | p = 0.32 | p = 0.12 | |||
| Country: Th. | -0.31 (-0.44, -0.18) | -0.25 (-0.37, -0.13) | -0.34 (-0.46, -0.22) | -0.35 (-0.48, -0.23) | ||
| p = 0.000004 | p = 0.00003 | p = 0.0000001 | p = 0.00000004 | |||
| Country: Ch. | 0.24 (0.06, 0.42) | -0.09 (-0.22, 0.03) | 0.20 (0.04, 0.37) | 0.20 (0.03, 0.37) | ||
| p = 0.01 | p = 0.14 | p = 0.02 | p = 0.02 | |||
| Country: Va. | -0.12 (-0.29, 0.05) | -0.01 (-0.14, 0.11) | -0.08 (-0.24, 0.08) | -0.05 (-0.21, 0.12) | ||
| p = 0.17 | p = 0.84 | p = 0.33 | p = 0.56 | |||
| Scale: Hallucinations × Country: Gh. | 0.11 (-0.01, 0.23) | 0.09 (-0.02, 0.19) | 0.10 (-0.02, 0.22) | 0.10 (-0.02, 0.23) | ||
| p = 0.09 | p = 0.10 | p = 0.12 | p = 0.12 | |||
| Scale: Hallucinations × Country: Th. | -0.12 (-0.23, -0.02) | -0.17 (-0.27, -0.08) | -0.12 (-0.23, -0.01) | -0.12 (-0.23, -0.01) | ||
| p = 0.03 | p = 0.001 | p = 0.04 | p = 0.04 | |||
| Scale: Hallucinations × Country: Ch. | -0.26 (-0.41, -0.12) | -0.07 (-0.18, 0.03) | -0.27 (-0.42, -0.12) | -0.27 (-0.42, -0.12) | ||
| p = 0.0005 | p = 0.16 | p = 0.0004 | p = 0.0004 | |||
| Scale: Hallucinations × Country: Va. | -0.04 (-0.17, 0.10) | -0.08 (-0.19, 0.02) | -0.04 (-0.18, 0.10) | -0.03 (-0.18, 0.12) | ||
| p = 0.60 | p = 0.13 | p = 0.58 | p = 0.69 | |||
| Scale: Hallucinations × Porosity Vignettes | -0.01 (-0.07, 0.04) | -0.07 (-0.13, -0.005) | -0.07 (-0.14, -0.01) | -0.07 (-0.14, -0.01) | ||
| p = 0.60 | p = 0.04 | p = 0.03 | p = 0.04 | |||
| Gender: male | -0.06 (-0.12, 0.005) | |||||
| p = 0.08 | ||||||
| Age | -0.05 (-0.12, 0.02) | |||||
| p = 0.17 | ||||||
| Scale: Hallucinations × Absorption | 0.01 (-0.04, 0.07) | 0.01 (-0.04, 0.06) | 0.02 (-0.05, 0.08) | 0.02 (-0.05, 0.09) | ||
| p = 0.63 | p = 0.61 | p = 0.61 | p = 0.59 | |||
| Country: Gh. × Porosity Vignettes | -0.12 (-0.26, 0.01) | -0.10 (-0.23, 0.03) | -0.10 (-0.22, 0.03) | |||
| p = 0.08 | p = 0.12 | p = 0.13 | ||||
| Country: Th. × Porosity Vignettes | -0.12 (-0.27, 0.02) | -0.15 (-0.28, -0.01) | -0.15 (-0.29, -0.02) | |||
| p = 0.10 | p = 0.04 | p = 0.03 | ||||
| Country: Ch. × Porosity Vignettes | 0.28 (0.09, 0.47) | 0.32 (0.14, 0.49) | 0.30 (0.12, 0.48) | |||
| p = 0.005 | p = 0.001 | p = 0.001 | ||||
| Country: Va. × Porosity Vignettes | -0.33 (-0.50, -0.15) | -0.31 (-0.47, -0.14) | -0.33 (-0.50, -0.16) | |||
| p = 0.0003 | p = 0.0003 | p = 0.0002 | ||||
| Scale: Hallucinations × Country: Gh. × Porosity Vignettes | 0.16 (0.05, 0.27) | 0.15 (0.04, 0.27) | 0.15 (0.04, 0.27) | |||
| p = 0.005 | p = 0.01 | p = 0.01 | ||||
| Scale: Hallucinations × Country: Th. × Porosity Vignettes | -0.05 (-0.16, 0.07) | -0.04 (-0.16, 0.08) | -0.04 (-0.16, 0.08) | |||
| p = 0.43 | p = 0.51 | p = 0.51 | ||||
| Scale: Hallucinations × Country: Ch. × Porosity Vignettes | -0.30 (-0.46, -0.15) | -0.30 (-0.46, -0.14) | -0.29 (-0.45, -0.13) | |||
| p = 0.0002 | p = 0.0003 | p = 0.0004 | ||||
| Scale: Hallucinations × Country: Va. × Porosity Vignettes | 0.11 (-0.03, 0.26) | 0.11 (-0.03, 0.26) | 0.12 (-0.04, 0.27) | |||
| p = 0.12 | p = 0.13 | p = 0.14 | ||||
| Country: Gh. × Absorption | -0.09 (-0.21, 0.04) | -0.07 (-0.20, 0.07) | -0.05 (-0.18, 0.08) | |||
| p = 0.17 | p = 0.33 | p = 0.47 | ||||
| Country: Th. × Absorption | -0.01 (-0.13, 0.11) | -0.01 (-0.14, 0.11) | 0.001 (-0.12, 0.12) | |||
| p = 0.91 | p = 0.83 | p = 0.99 | ||||
| Country: Ch. × Absorption | -0.03 (-0.16, 0.09) | 0.07 (-0.12, 0.25) | 0.09 (-0.09, 0.27) | |||
| p = 0.62 | p = 0.49 | p = 0.33 | ||||
| Country: Va. × Absorption | -0.11 (-0.23, 0.02) | -0.04 (-0.20, 0.12) | -0.05 (-0.22, 0.11) | |||
| p = 0.11 | p = 0.65 | p = 0.53 | ||||
| Scale: Hallucinations × Country: Gh. × Absorption | 0.05 (-0.05, 0.15) | 0.02 (-0.10, 0.14) | 0.02 (-0.10, 0.14) | |||
| p = 0.33 | p = 0.73 | p = 0.75 | ||||
| Scale: Hallucinations × Country: Th. × Absorption | -0.04 (-0.13, 0.06) | -0.02 (-0.13, 0.09) | -0.02 (-0.13, 0.09) | |||
| p = 0.48 | p = 0.73 | p = 0.73 | ||||
| Scale: Hallucinations × Country: Ch. × Absorption | -0.01 (-0.11, 0.09) | 0.02 (-0.15, 0.18) | 0.01 (-0.15, 0.18) | |||
| p = 0.82 | p = 0.86 | p = 0.89 | ||||
| Scale: Hallucinations × Country: Va. × Absorption | -0.01 (-0.12, 0.10) | -0.001 (-0.14, 0.14) | 0.03 (-0.12, 0.18) | |||
| p = 0.86 | p = 1.00 | p = 0.73 | ||||
| Scale: Hallucinations × Porosity Vignettes × Absorption | -0.02 (-0.09, 0.04) | -0.02 (-0.09, 0.04) | ||||
| p = 0.53 | p = 0.49 | |||||
| Country: Gh. × Porosity Vignettes × Absorption | -0.11 (-0.23, 0.01) | -0.13 (-0.25, -0.003) | ||||
| p = 0.08 | p = 0.05 | |||||
| Country: Th. × Porosity Vignettes × Absorption | 0.04 (-0.09, 0.18) | 0.03 (-0.11, 0.16) | ||||
| p = 0.55 | p = 0.69 | |||||
| Country: Ch. × Porosity Vignettes × Absorption | 0.14 (-0.05, 0.34) | 0.13 (-0.06, 0.32) | ||||
| p = 0.15 | p = 0.17 | |||||
| Country: Va. × Porosity Vignettes × Absorption | -0.07 (-0.22, 0.09) | -0.05 (-0.21, 0.11) | ||||
| p = 0.41 | p = 0.56 | |||||
| Scale: Hallucinations × Country: Gh. × Porosity Vignettes × Absorption | 0.04 (-0.07, 0.15) | 0.04 (-0.07, 0.16) | ||||
| p = 0.46 | p = 0.44 | |||||
| Scale: Hallucinations × Country: Th. × Porosity Vignettes × Absorption | -0.04 (-0.16, 0.08) | -0.04 (-0.16, 0.08) | ||||
| p = 0.49 | p = 0.52 | |||||
| Scale: Hallucinations × Country: Ch. × Porosity Vignettes × Absorption | 0.04 (-0.13, 0.21) | 0.05 (-0.12, 0.22) | ||||
| p = 0.66 | p = 0.59 | |||||
| Scale: Hallucinations × Country: Va. × Porosity Vignettes × Absorption | -0.004 (-0.14, 0.14) | -0.03 (-0.18, 0.12) | ||||
| p = 0.96 | p = 0.70 | |||||
| Constant | -0.00 (-0.06, 0.06) | 0.00 (-0.06, 0.06) | 0.10 (0.03, 0.18) | 0.005 (-0.06, 0.07) | 0.11 (0.03, 0.18) | 0.09 (0.02, 0.16) |
| p = 1.00 | p = 1.00 | p = 0.01 | p = 0.88 | p = 0.004 | p = 0.02 | |
| Observations | 1,010 | 1,010 | 1,010 | 1,010 | 1,010 | 980 |
| Log Likelihood | -1,380.61 | -1,372.19 | -1,351.32 | -1,365.54 | -1,347.04 | -1,307.43 |
| Akaike Inf. Crit. | 2,773.23 | 2,756.37 | 2,746.63 | 2,775.07 | 2,778.08 | 2,702.87 |
| Bayesian Inf. Crit. | 2,802.74 | 2,785.88 | 2,854.82 | 2,883.26 | 2,984.62 | 2,917.92 |
rsq_table_fun(list(r03_secular, #r04_secular,
r05_secular, r06_secular, #r07_secular,
r08_secular, r09_secular, #r10_secular,
r11_secular #, r12_secular
))
| R-squared Type | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Marginal | 0.09 | 0.11 | 0.20 | 0.18 | 0.27 | 0.27 |
| Conditional | 0.29 | 0.29 | 0.36 | 0.33 | 0.36 | 0.34 |
table_s48 <- stargazer(#r03_secular,
r04_secular, r05_secular, #r06_secular,
r07_secular, r08_secular, #r09_secular,
r10_secular, #r11_secular,
r12_secular,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Scale`$",
"^Absorption$",
"^`Porosity Scale`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s48),
file = "./stargazer_tables/table_s48.html")
htmltools::includeHTML("./stargazer_tables/table_s48.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Porosity Scale | 0.33 (0.26, 0.39) | 0.45 (0.37, 0.53) | 0.37 (0.29, 0.45) | 0.36 (0.28, 0.45) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.34 (0.27, 0.40) | 0.33 (0.27, 0.40) | 0.27 (0.19, 0.35) | 0.26 (0.18, 0.34) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Porosity Scale × Absorption | 0.05 (-0.03, 0.12) | 0.04 (-0.04, 0.12) | ||||
| p = 0.25 | p = 0.32 | |||||
| Scale: Hallucinations | -0.00 (-0.05, 0.05) | 0.00 (-0.05, 0.05) | -0.10 (-0.17, -0.03) | 0.002 (-0.05, 0.05) | -0.12 (-0.19, -0.04) | -0.11 (-0.19, -0.04) |
| p = 1.00 | p = 1.00 | p = 0.005 | p = 0.96 | p = 0.003 | p = 0.004 | |
| Country: Gh. | 0.05 (-0.10, 0.20) | 0.24 (0.12, 0.37) | 0.11 (-0.03, 0.25) | 0.15 (0.004, 0.30) | ||
| p = 0.54 | p = 0.0002 | p = 0.13 | p = 0.05 | |||
| Country: Th. | -0.25 (-0.38, -0.11) | -0.25 (-0.37, -0.13) | -0.27 (-0.40, -0.14) | -0.27 (-0.41, -0.14) | ||
| p = 0.0004 | p = 0.00003 | p = 0.00004 | p = 0.0001 | |||
| Country: Ch. | 0.39 (0.21, 0.58) | -0.09 (-0.22, 0.03) | 0.33 (0.14, 0.51) | 0.31 (0.12, 0.50) | ||
| p = 0.00004 | p = 0.14 | p = 0.001 | p = 0.002 | |||
| Country: Va. | -0.42 (-0.64, -0.19) | -0.01 (-0.14, 0.11) | -0.35 (-0.57, -0.14) | -0.33 (-0.55, -0.11) | ||
| p = 0.0003 | p = 0.84 | p = 0.002 | p = 0.004 | |||
| Scale: Hallucinations × Country: Gh. | 0.20 (0.08, 0.32) | 0.09 (-0.02, 0.19) | 0.23 (0.10, 0.36) | 0.23 (0.10, 0.36) | ||
| p = 0.002 | p = 0.10 | p = 0.0005 | p = 0.001 | |||
| Scale: Hallucinations × Country: Th. | -0.13 (-0.24, -0.02) | -0.17 (-0.27, -0.08) | -0.12 (-0.24, -0.01) | -0.13 (-0.24, -0.01) | ||
| p = 0.03 | p = 0.001 | p = 0.04 | p = 0.04 | |||
| Scale: Hallucinations × Country: Ch. | -0.35 (-0.51, -0.20) | -0.07 (-0.18, 0.03) | -0.41 (-0.58, -0.24) | -0.41 (-0.58, -0.24) | ||
| p = 0.00001 | p = 0.16 | p = 0.000002 | p = 0.000003 | |||
| Scale: Hallucinations × Country: Va. | -0.05 (-0.24, 0.13) | -0.08 (-0.19, 0.02) | -0.05 (-0.24, 0.15) | -0.03 (-0.23, 0.16) | ||
| p = 0.58 | p = 0.13 | p = 0.64 | p = 0.74 | |||
| Scale: Hallucinations × Porosity Scale | -0.07 (-0.12, -0.01) | -0.13 (-0.20, -0.06) | -0.15 (-0.22, -0.07) | -0.15 (-0.22, -0.08) | ||
| p = 0.02 | p = 0.0003 | p = 0.0001 | p = 0.0001 | |||
| Gender: male | -0.01 (-0.08, 0.05) | |||||
| p = 0.65 | ||||||
| Age | -0.06 (-0.13, 0.01) | |||||
| p = 0.10 | ||||||
| Scale: Hallucinations × Absorption | 0.01 (-0.04, 0.07) | 0.01 (-0.04, 0.06) | 0.06 (-0.02, 0.13) | 0.05 (-0.02, 0.13) | ||
| p = 0.63 | p = 0.61 | p = 0.14 | p = 0.17 | |||
| Country: Gh. × Porosity Scale | -0.27 (-0.42, -0.13) | -0.25 (-0.38, -0.11) | -0.24 (-0.38, -0.10) | |||
| p = 0.0003 | p = 0.001 | p = 0.001 | ||||
| Country: Th. × Porosity Scale | -0.10 (-0.25, 0.06) | -0.09 (-0.24, 0.05) | -0.09 (-0.24, 0.05) | |||
| p = 0.23 | p = 0.22 | p = 0.22 | ||||
| Country: Ch. × Porosity Scale | 0.26 (0.08, 0.44) | 0.25 (0.07, 0.43) | 0.25 (0.07, 0.43) | |||
| p = 0.005 | p = 0.01 | p = 0.01 | ||||
| Country: Va. × Porosity Scale | -0.12 (-0.33, 0.08) | -0.11 (-0.30, 0.09) | -0.10 (-0.30, 0.10) | |||
| p = 0.25 | p = 0.28 | p = 0.34 | ||||
| Scale: Hallucinations × Country: Gh. × Porosity Scale | 0.11 (-0.01, 0.23) | 0.11 (-0.01, 0.24) | 0.12 (-0.01, 0.24) | |||
| p = 0.07 | p = 0.08 | p = 0.08 | ||||
| Scale: Hallucinations × Country: Th. × Porosity Scale | -0.08 (-0.20, 0.05) | -0.06 (-0.19, 0.07) | -0.06 (-0.20, 0.07) | |||
| p = 0.24 | p = 0.36 | p = 0.36 | ||||
| Scale: Hallucinations × Country: Ch. × Porosity Scale | -0.34 (-0.49, -0.19) | -0.39 (-0.55, -0.23) | -0.38 (-0.54, -0.22) | |||
| p = 0.00001 | p = 0.000002 | p = 0.000004 | ||||
| Scale: Hallucinations × Country: Va. × Porosity Scale | 0.21 (0.04, 0.38) | 0.23 (0.05, 0.41) | 0.23 (0.05, 0.41) | |||
| p = 0.02 | p = 0.02 | p = 0.02 | ||||
| Country: Gh. × Absorption | -0.09 (-0.21, 0.04) | -0.004 (-0.14, 0.13) | 0.003 (-0.13, 0.14) | |||
| p = 0.17 | p = 0.96 | p = 0.97 | ||||
| Country: Th. × Absorption | -0.01 (-0.13, 0.11) | 0.04 (-0.09, 0.16) | 0.04 (-0.09, 0.17) | |||
| p = 0.91 | p = 0.58 | p = 0.53 | ||||
| Country: Ch. × Absorption | -0.03 (-0.16, 0.09) | -0.07 (-0.26, 0.12) | -0.05 (-0.24, 0.14) | |||
| p = 0.62 | p = 0.48 | p = 0.60 | ||||
| Country: Va. × Absorption | -0.11 (-0.23, 0.02) | -0.15 (-0.36, 0.06) | -0.15 (-0.37, 0.06) | |||
| p = 0.11 | p = 0.16 | p = 0.16 | ||||
| Scale: Hallucinations × Country: Gh. × Absorption | 0.05 (-0.05, 0.15) | 0.03 (-0.09, 0.15) | 0.04 (-0.09, 0.16) | |||
| p = 0.33 | p = 0.60 | p = 0.56 | ||||
| Scale: Hallucinations × Country: Th. × Absorption | -0.04 (-0.13, 0.06) | -0.04 (-0.15, 0.08) | -0.03 (-0.15, 0.08) | |||
| p = 0.48 | p = 0.53 | p = 0.59 | ||||
| Scale: Hallucinations × Country: Ch. × Absorption | -0.01 (-0.11, 0.09) | 0.11 (-0.05, 0.28) | 0.12 (-0.05, 0.29) | |||
| p = 0.82 | p = 0.19 | p = 0.18 | ||||
| Scale: Hallucinations × Country: Va. × Absorption | -0.01 (-0.12, 0.10) | -0.08 (-0.27, 0.11) | -0.06 (-0.26, 0.13) | |||
| p = 0.86 | p = 0.40 | p = 0.53 | ||||
| Scale: Hallucinations × Porosity Scale × Absorption | 0.01 (-0.05, 0.08) | 0.01 (-0.06, 0.08) | ||||
| p = 0.70 | p = 0.81 | |||||
| Country: Gh. × Porosity Scale × Absorption | -0.14 (-0.27, -0.01) | -0.14 (-0.27, -0.01) | ||||
| p = 0.04 | p = 0.04 | |||||
| Country: Th. × Porosity Scale × Absorption | 0.07 (-0.07, 0.21) | 0.08 (-0.06, 0.22) | ||||
| p = 0.32 | p = 0.29 | |||||
| Country: Ch. × Porosity Scale × Absorption | -0.02 (-0.18, 0.15) | -0.004 (-0.17, 0.16) | ||||
| p = 0.86 | p = 0.97 | |||||
| Country: Va. × Porosity Scale × Absorption | 0.04 (-0.15, 0.23) | 0.04 (-0.15, 0.23) | ||||
| p = 0.67 | p = 0.66 | |||||
| Scale: Hallucinations × Country: Gh. × Porosity Scale × Absorption | -0.05 (-0.17, 0.06) | -0.05 (-0.17, 0.07) | ||||
| p = 0.37 | p = 0.42 | |||||
| Scale: Hallucinations × Country: Th. × Porosity Scale × Absorption | 0.02 (-0.10, 0.15) | 0.03 (-0.10, 0.16) | ||||
| p = 0.73 | p = 0.63 | |||||
| Scale: Hallucinations × Country: Ch. × Porosity Scale × Absorption | 0.05 (-0.10, 0.20) | 0.06 (-0.09, 0.21) | ||||
| p = 0.52 | p = 0.44 | |||||
| Scale: Hallucinations × Country: Va. × Porosity Scale × Absorption | 0.01 (-0.16, 0.18) | 0.002 (-0.17, 0.17) | ||||
| p = 0.94 | p = 0.98 | |||||
| Constant | 0.00 (-0.06, 0.06) | 0.00 (-0.06, 0.06) | 0.10 (0.01, 0.18) | 0.005 (-0.06, 0.07) | 0.08 (0.002, 0.17) | 0.08 (-0.004, 0.16) |
| p = 1.00 | p = 1.00 | p = 0.03 | p = 0.88 | p = 0.05 | p = 0.07 | |
| Observations | 1,010 | 1,010 | 1,010 | 1,010 | 1,010 | 980 |
| Log Likelihood | -1,371.56 | -1,372.19 | -1,328.58 | -1,365.54 | -1,319.94 | -1,290.48 |
| Akaike Inf. Crit. | 2,755.12 | 2,756.37 | 2,701.17 | 2,775.07 | 2,723.89 | 2,668.97 |
| Bayesian Inf. Crit. | 2,784.63 | 2,785.88 | 2,809.36 | 2,883.26 | 2,930.43 | 2,884.02 |
rsq_table_fun(list(#r03_secular,
r04_secular, r05_secular, #r06_secular,
r07_secular, r08_secular, #r09_secular,
r10_secular, #r11_secular,
r12_secular))
| R-squared Type | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Marginal | 0.11 | 0.11 | 0.23 | 0.18 | 0.31 | 0.30 |
| Conditional | 0.30 | 0.29 | 0.38 | 0.33 | 0.38 | 0.37 |
r13_secular <- lmer(Score ~ Scale
+ (1 | Country/subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r14_secular <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | Country/subject_id),
# + (1 + `Porosity Vignettes` | Country), # adding to above, failed to converge
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r15_secular <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | Country/subject_id),
# + (1 + `Porosity Scale` | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r16_secular <- lmer(Score ~ Scale * Absorption
+ (1 | Country/subject_id),
# + (1 + Absorption | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r17_secular <- lmer(Score ~ Scale * `Porosity Vignettes` * Absorption
+ (1 | Country/subject_id),
# + (1 + `Porosity Vignettes` * Absorption | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r18_secular <- lmer(Score ~ Scale * `Porosity Scale` * Absorption
+ (1 | Country/subject_id),
# + (1 + `Porosity Scale` * Absorption | Country), # adding to above, perfectly correlated ranfx
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r19_secular <- lmer(Score ~ Scale * `Porosity Vignettes` * Absorption
+ Gender + Age
+ (1 | Country/subject_id),
# + (1 + `Porosity Vignettes` * Absorption + Gender + Age | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
r20_secular <- lmer(Score ~ Scale * `Porosity Scale` * Absorption
+ Gender + Age
+ (1 | Country/subject_id),
# + (1 + `Porosity Scale` * Absorption + Gender + Age | Country),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular)
table_s49 <- stargazer(r13_secular, r14_secular, #r15_secular,
r16_secular, r17_secular, #r18_secular,
r19_secular, #r20_secular,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^Absorption$",
"^`Porosity Vignettes`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s49),
file = "./stargazer_tables/table_s49.html")
htmltools::includeHTML("./stargazer_tables/table_s49.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.35 (0.27, 0.42) | 0.27 (0.20, 0.34) | 0.27 (0.21, 0.34) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.34 (0.27, 0.40) | 0.28 (0.22, 0.34) | 0.27 (0.21, 0.33) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | |||
| Porosity Vignettes × Absorption | -0.04 (-0.10, 0.02) | -0.04 (-0.10, 0.02) | |||
| p = 0.16 | p = 0.23 | ||||
| Scale: Hallucinations | 0.00 (-0.05, 0.05) | 0.00 (-0.05, 0.05) | 0.00 (-0.05, 0.05) | 0.001 (-0.05, 0.05) | -0.002 (-0.06, 0.05) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 0.99 | p = 0.94 | |
| Scale: Hallucinations × Porosity Vignettes | -0.01 (-0.07, 0.04) | -0.02 (-0.07, 0.04) | -0.02 (-0.07, 0.04) | ||
| p = 0.60 | p = 0.52 | p = 0.58 | |||
| Gender: male | -0.05 (-0.11, 0.01) | ||||
| p = 0.12 | |||||
| Age | -0.05 (-0.12, 0.02) | ||||
| p = 0.16 | |||||
| Scale: Hallucinations × Absorption | 0.01 (-0.04, 0.07) | 0.02 (-0.04, 0.07) | 0.01 (-0.05, 0.06) | ||
| p = 0.63 | p = 0.55 | p = 0.76 | |||
| Scale: Hallucinations × Porosity Vignettes × Absorption | -0.003 (-0.06, 0.05) | -0.0002 (-0.05, 0.05) | |||
| p = 0.91 | p = 1.00 | ||||
| Constant | 0.004 (-0.16, 0.17) | -0.0005 (-0.17, 0.17) | 0.004 (-0.16, 0.17) | 0.01 (-0.15, 0.17) | -0.01 (-0.16, 0.15) |
| p = 0.97 | p = 1.00 | p = 0.97 | p = 0.91 | p = 0.93 | |
| Observations | 1,010 | 1,010 | 1,010 | 1,010 | 980 |
| Log Likelihood | -1,408.91 | -1,373.09 | -1,363.37 | -1,344.00 | -1,304.54 |
| Akaike Inf. Crit. | 2,827.82 | 2,760.18 | 2,740.75 | 2,710.00 | 2,635.09 |
| Bayesian Inf. Crit. | 2,852.41 | 2,794.60 | 2,775.17 | 2,764.09 | 2,698.63 |
rsq_table_fun(list(r13_secular, r14_secular, #r15_secular,
r16_secular, r17_secular, #r18_secular,
r19_secular #, r20_secular
))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.00 | 0.12 | 0.11 | 0.18 | 0.18 |
| Conditional | 0.29 | 0.31 | 0.29 | 0.30 | 0.28 |
table_s50 <- stargazer(r13_secular, #r14_secular,
r15_secular, r16_secular, #r17_secular,
r18_secular, #r19_secular,
r20_secular,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Scale`$",
"^Absorption$",
"^`Porosity Scale`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s50),
file = "./stargazer_tables/table_s50.html")
htmltools::includeHTML("./stargazer_tables/table_s50.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Scale | 0.45 (0.37, 0.53) | 0.37 (0.29, 0.44) | 0.35 (0.28, 0.43) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | |||
| Absorption | 0.34 (0.27, 0.40) | 0.27 (0.21, 0.33) | 0.26 (0.20, 0.32) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | |||
| Porosity Scale × Absorption | 0.01 (-0.05, 0.06) | -0.005 (-0.06, 0.05) | |||
| p = 0.80 | p = 0.87 | ||||
| Scale: Hallucinations | 0.00 (-0.05, 0.05) | -0.00 (-0.05, 0.05) | 0.00 (-0.05, 0.05) | -0.0004 (-0.05, 0.05) | -0.003 (-0.06, 0.05) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 0.99 | p = 0.90 | |
| Scale: Hallucinations × Porosity Scale | -0.07 (-0.12, -0.01) | -0.07 (-0.12, -0.02) | -0.07 (-0.12, -0.02) | ||
| p = 0.02 | p = 0.01 | p = 0.02 | |||
| Gender: male | -0.01 (-0.08, 0.05) | ||||
| p = 0.65 | |||||
| Age | -0.06 (-0.13, 0.01) | ||||
| p = 0.08 | |||||
| Scale: Hallucinations × Absorption | 0.01 (-0.04, 0.07) | 0.03 (-0.03, 0.08) | 0.02 (-0.04, 0.07) | ||
| p = 0.63 | p = 0.34 | p = 0.50 | |||
| Scale: Hallucinations × Porosity Scale × Absorption | 0.002 (-0.05, 0.05) | 0.001 (-0.05, 0.05) | |||
| p = 0.93 | p = 0.97 | ||||
| Constant | 0.004 (-0.16, 0.17) | -0.005 (-0.26, 0.25) | 0.004 (-0.16, 0.17) | -0.005 (-0.22, 0.21) | -0.01 (-0.20, 0.19) |
| p = 0.97 | p = 0.97 | p = 0.97 | p = 0.97 | p = 0.94 | |
| Observations | 1,010 | 1,010 | 1,010 | 1,010 | 980 |
| Log Likelihood | -1,408.91 | -1,353.88 | -1,363.37 | -1,326.72 | -1,291.91 |
| Akaike Inf. Crit. | 2,827.82 | 2,721.76 | 2,740.75 | 2,675.44 | 2,609.82 |
| Bayesian Inf. Crit. | 2,852.41 | 2,756.18 | 2,775.17 | 2,729.53 | 2,673.36 |
rsq_table_fun(list(r13_secular, #r14_secular,
r15_secular, r16_secular, #r17_secular,
r18_secular, #r19_secular
r20_secular
))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.00 | 0.18 | 0.11 | 0.23 | 0.22 |
| Conditional | 0.29 | 0.37 | 0.29 | 0.35 | 0.32 |
r21_secular_us <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "US") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
r21_secular_gh <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Ghana") %>%
mutate_at(vars(Score, ,`Porosity Vignettes`), ~ scale(.)))
r21_secular_th <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Thailand") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
r21_secular_ch <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "China") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
r21_secular_vt <- lmer(Score ~ Scale * `Porosity Vignettes`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Vanuatu") %>%
mutate_at(vars(Score, `Porosity Vignettes`), ~ scale(.)))
table_s51 <- stargazer(r21_secular_us, r21_secular_gh, r21_secular_th,
r21_secular_ch, r21_secular_vt,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s51),
file = "./stargazer_tables/table_s51.html")
htmltools::includeHTML("./stargazer_tables/table_s51.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.53 (0.41, 0.66) | 0.21 (0.07, 0.35) | 0.21 (0.06, 0.35) | 0.39 (0.26, 0.52) | 0.01 (-0.16, 0.17) |
| p = 0.00 | p = 0.003 | p = 0.005 | p = 0.00 | p = 0.93 | |
| Scale: Hallucinations | 0.20 (0.09, 0.30) | 0.09 (-0.04, 0.22) | -0.20 (-0.30, -0.09) | -0.08 (-0.19, 0.04) | -0.10 (-0.22, 0.02) |
| p = 0.0002 | p = 0.18 | p = 0.0002 | p = 0.19 | p = 0.12 | |
| Scale: Hallucinations × Porosity Vignettes | 0.01 (-0.09, 0.11) | 0.09 (-0.04, 0.22) | -0.11 (-0.22, -0.01) | -0.24 (-0.35, -0.12) | 0.04 (-0.08, 0.16) |
| p = 0.90 | p = 0.18 | p = 0.04 | p = 0.0001 | p = 0.53 | |
| Constant | -0.00 (-0.13, 0.13) | -0.00 (-0.14, 0.14) | -0.00 (-0.14, 0.14) | -0.00 (-0.13, 0.13) | -0.00 (-0.17, 0.17) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 204 | 200 | 222 | 200 | 184 |
| Log Likelihood | -254.85 | -283.67 | -305.06 | -265.61 | -261.90 |
| Akaike Inf. Crit. | 521.70 | 579.33 | 622.12 | 543.22 | 535.81 |
| Bayesian Inf. Crit. | 541.61 | 599.12 | 642.53 | 563.01 | 555.10 |
rsq_table_fun(list(r21_secular_us, r21_secular_gh, r21_secular_th,
r21_secular_ch, r21_secular_vt))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.32 | 0.06 | 0.09 | 0.21 | 0.01 |
| Conditional | 0.46 | 0.12 | 0.38 | 0.32 | 0.31 |
r22_secular_us <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "US") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_secular_gh <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Ghana") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_secular_th <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Thailand") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_secular_ch <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "China") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
r22_secular_vt <- lmer(Score ~ Scale * `Porosity Scale`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Vanuatu") %>%
mutate_at(vars(Score, `Porosity Scale`), ~ scale(.)))
table_s52 <- stargazer(r22_secular_us, r22_secular_gh, r22_secular_th,
r22_secular_ch, r22_secular_vt,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Scale`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s52),
file = "./stargazer_tables/table_s52.html")
htmltools::includeHTML("./stargazer_tables/table_s52.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Scale | 0.52 (0.40, 0.65) | 0.16 (0.01, 0.30) | 0.31 (0.18, 0.45) | 0.49 (0.37, 0.61) | 0.23 (0.07, 0.39) |
| p = 0.00 | p = 0.04 | p = 0.00001 | p = 0.00 | p = 0.01 | |
| Scale: Hallucinations | 0.20 (0.09, 0.30) | 0.09 (-0.04, 0.22) | -0.20 (-0.30, -0.10) | -0.08 (-0.18, 0.03) | -0.10 (-0.22, 0.02) |
| p = 0.0002 | p = 0.18 | p = 0.0002 | p = 0.16 | p = 0.12 | |
| Scale: Hallucinations × Porosity Scale | -0.02 (-0.13, 0.08) | -0.01 (-0.15, 0.12) | -0.18 (-0.28, -0.08) | -0.32 (-0.43, -0.22) | 0.05 (-0.07, 0.18) |
| p = 0.64 | p = 0.84 | p = 0.0005 | p = 0.00 | p = 0.38 | |
| Constant | -0.00 (-0.13, 0.13) | -0.00 (-0.14, 0.14) | 0.00 (-0.14, 0.14) | -0.00 (-0.12, 0.12) | -0.00 (-0.16, 0.16) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 204 | 200 | 222 | 200 | 184 |
| Log Likelihood | -255.66 | -286.66 | -296.13 | -246.83 | -257.99 |
| Akaike Inf. Crit. | 523.33 | 585.33 | 604.27 | 505.65 | 527.97 |
| Bayesian Inf. Crit. | 543.24 | 605.12 | 624.68 | 525.44 | 547.26 |
rsq_table_fun(list(r22_secular_us, r22_secular_gh, r22_secular_th,
r22_secular_ch, r22_secular_vt))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.31 | 0.03 | 0.17 | 0.35 | 0.06 |
| Conditional | 0.46 | 0.11 | 0.42 | 0.42 | 0.32 |
r23_secular_us <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "US") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_secular_gh <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Ghana") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_secular_th <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Thailand") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_secular_ch <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "China") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
r23_secular_vt <- lmer(Score ~ Scale * `Absorption`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_fortab_long_secular %>% filter(Country == "Vanuatu") %>%
mutate_at(vars(Score, `Absorption`), ~ scale(.)))
table_s53 <- stargazer(r23_secular_us, r23_secular_gh, r23_secular_th,
r23_secular_ch, r23_secular_vt,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s53),
file = "./stargazer_tables/table_s53.html")
htmltools::includeHTML("./stargazer_tables/table_s53.html")
| Score | |||||
| (1) | (2) | (3) | (4) | (5) | |
| Absorption | 0.45 (0.31, 0.59) | 0.25 (0.11, 0.39) | 0.38 (0.25, 0.51) | 0.32 (0.18, 0.46) | 0.28 (0.12, 0.43) |
| p = 0.00 | p = 0.0004 | p = 0.00000003 | p = 0.00001 | p = 0.001 | |
| Scale: Hallucinations | 0.20 (0.09, 0.30) | 0.09 (-0.04, 0.22) | -0.20 (-0.31, -0.09) | -0.08 (-0.20, 0.05) | -0.10 (-0.22, 0.02) |
| p = 0.0002 | p = 0.18 | p = 0.0003 | p = 0.23 | p = 0.12 | |
| Scale: Hallucinations × Absorption | 0.02 (-0.09, 0.12) | 0.07 (-0.06, 0.20) | -0.03 (-0.13, 0.08) | 0.001 (-0.12, 0.13) | 0.005 (-0.12, 0.13) |
| p = 0.76 | p = 0.33 | p = 0.64 | p = 0.99 | p = 0.95 | |
| Constant | -0.00 (-0.14, 0.14) | -0.00 (-0.14, 0.14) | 0.00 (-0.13, 0.13) | -0.00 (-0.14, 0.14) | -0.00 (-0.16, 0.16) |
| p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | p = 1.00 | |
| Observations | 204 | 200 | 222 | 200 | 184 |
| Log Likelihood | -263.58 | -282.35 | -297.18 | -278.38 | -256.45 |
| Akaike Inf. Crit. | 539.16 | 576.69 | 606.37 | 568.76 | 524.89 |
| Bayesian Inf. Crit. | 559.06 | 596.48 | 626.78 | 588.55 | 544.18 |
rsq_table_fun(list(r23_secular_us, r23_secular_gh, r23_secular_th,
r23_secular_ch, r23_secular_vt))
| R-squared Type | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Marginal | 0.24 | 0.08 | 0.18 | 0.11 | 0.08 |
| Conditional | 0.46 | 0.11 | 0.35 | 0.21 | 0.31 |
d1_abs <- d1_byq %>%
select(subject_id, ends_with("_abs")) %>%
column_to_rownames("subject_id")
fa.parallel(d1_abs)
Parallel analysis suggests that the number of factors = 4 and the number of components = 3
d1_all_efa <- fa(d1_abs, nfactors = 4, rotate = "oblimin")
Loading required namespace: GPArotation
d1_all_loadings <- d1_all_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d1_all_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 1: All sites", x = "factor", y = "question")
d1_abs_us <- d1_byq %>%
filter(country == "US") %>%
select(subject_id, ends_with("_abs")) %>%
column_to_rownames("subject_id")
fa.parallel(d1_abs_us)
Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.The estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.NaNs produceddiag(.) had 0 or NA entries; non-finite result is doubtful
Parallel analysis suggests that the number of factors = 3 and the number of components = 1
d1_us_efa <- fa(d1_abs, nfactors = 3, rotate = "oblimin")
d1_us_loadings <- d1_us_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d1_us_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 1: US", x = "factor", y = "question")
d1_abs_gh <- d1_byq %>%
filter(country == "Ghana") %>%
select(subject_id, ends_with("_abs")) %>%
column_to_rownames("subject_id")
fa.parallel(d1_abs_gh)
Parallel analysis suggests that the number of factors = 2 and the number of components = 2
d1_gh_efa <- fa(d1_abs, nfactors = 2, rotate = "oblimin")
d1_gh_loadings <- d1_gh_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d1_gh_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 1: Ghana", x = "factor", y = "question")
d1_abs_th <- d1_byq %>%
filter(country == "Thailand") %>%
select(subject_id, ends_with("_abs")) %>%
column_to_rownames("subject_id")
fa.parallel(d1_abs_th)
Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.
Parallel analysis suggests that the number of factors = 1 and the number of components = 1
d1_th_efa <- fa(d1_abs, nfactors = 1, rotate = "oblimin")
d1_th_loadings <- d1_th_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d1_th_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 1: Thailand", x = "factor", y = "question")
d1_abs_ch <- d1_byq %>%
filter(country == "China") %>%
select(subject_id, ends_with("_abs")) %>%
column_to_rownames("subject_id")
fa.parallel(d1_abs_ch)
The estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.Matrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.
Parallel analysis suggests that the number of factors = 1 and the number of components = 1
d1_ch_efa <- fa(d1_abs, nfactors = 1, rotate = "oblimin")
d1_ch_loadings <- d1_ch_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d1_ch_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 1: China", x = "factor", y = "question")
d1_abs_vt <- d1_byq %>%
filter(country == "Vanuatu") %>%
select(subject_id, ends_with("_abs")) %>%
column_to_rownames("subject_id")
fa.parallel(d1_abs_vt)
the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was donethe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was donethe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was donethe standard deviation is zeroIn smc, smcs < 0 were set to .0
the standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was donethe standard deviation is zeroThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation 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standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was doneIn smc, smcs < 0 were set to .0
Matrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.the standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zerothe standard deviation is zeroMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneMatrix was not positive definite, smoothing was doneThe estimated weights for the factor scores are probably incorrect. Try a different factor score estimation method.
Parallel analysis suggests that the number of factors = 5 and the number of components = 4
d1_vt_efa <- fa(d1_abs, nfactors = 5, rotate = "oblimin")
d1_vt_loadings <- d1_vt_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d1_vt_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 1: Vanuatu", x = "factor", y = "question")
d3_abs <- d3_byq %>%
select(subj, question, response) %>%
filter(question %in% c("exwl_01", "exwl_02", "exwl_03", "exwl_04", "exwl_05", "exwl_06",
"exwl_07", "exwl_08", "exwl_09", "exwl_10", "exwl_11", "exwl_12",
"exwl_13", "exwl_14", "exwl_15", "exwl_16", "exwl_17", "exwl_18",
"exwl_19", "exwl_20", "exwl_21", "exwl_22", "exwl_23", "exwl_24",
"exwl_25", "exwl_26", "exwl_27", "exwl_28", "exwl_29", "exwl_30",
"exwl_31", "exwl_32", "exwl_33", "exwl_34")) %>%
mutate(question = factor(
question,
levels = c("exwl_01", "exwl_02", "exwl_03", "exwl_04",
"exwl_05", "exwl_06", "exwl_07", "exwl_08",
"exwl_09", "exwl_10", "exwl_11", "exwl_12",
"exwl_13", "exwl_14", "exwl_15", "exwl_16",
"exwl_17", "exwl_18", "exwl_19", "exwl_20",
"exwl_21", "exwl_22", "exwl_23", "exwl_24",
"exwl_25", "exwl_26", "exwl_27", "exwl_28",
"exwl_29", "exwl_30", "exwl_31", "exwl_32",
"exwl_33", "exwl_34"),
labels = c("childexp", "poeticlanguage", "forgetsurrounding", "starepicture",
"mindenvelopworld", "cloudshapes", "vividdaydream", "mysticalexp",
"stepoutsidemyself", "textures", "doublyreal", "caughtupinmusic",
"heavybody", "sensepresence", "woodfireimagine", "immersednature",
"colormeaning", "wanderthoughtstask", "clearpastexp", "meaninglesstoothers",
"actinginplay", "visualthoughts", "delightsmallthings", "organmusic",
"changenoise", "vividsmellmemories", "synesthesiasound", "predictwords",
"physicalmemories", "fascinatingvoice", "invisiblepresence", "sponthoughtsimages",
"synesthesiasmell", "emosunset"))) %>%
spread(question, response) %>%
column_to_rownames("subj")
fa.parallel(d3_abs)
Parallel analysis suggests that the number of factors = 5 and the number of components = 4
d3_all_efa <- fa(d3_abs, nfactors = 6, rotate = "oblimin")
d3_all_loadings <- d3_all_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d3_all_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 3: All sites", x = "factor", y = "question")
d3_abs_us <- d3_abs %>%
rownames_to_column("subj") %>%
filter(subj %in% c(d3_byq %>% filter(ctry == "us") %>% distinct(subj) %>% pull(subj))) %>%
column_to_rownames("subj")
fa.parallel(d3_abs_us)
Parallel analysis suggests that the number of factors = 4 and the number of components = 3
d3_us_efa <- fa(d3_abs, nfactors = 4, rotate = "oblimin")
d3_us_loadings <- d3_us_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d3_us_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 3: US", x = "factor", y = "question")
d3_abs_gh <- d3_abs %>%
rownames_to_column("subj") %>%
filter(subj %in% c(d3_byq %>% filter(ctry == "ghana") %>% distinct(subj) %>% pull(subj))) %>%
column_to_rownames("subj")
fa.parallel(d3_abs_gh)
Parallel analysis suggests that the number of factors = 2 and the number of components = 1
d3_gh_efa <- fa(d3_abs, nfactors = 2, rotate = "oblimin")
d3_gh_loadings <- d3_gh_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d3_gh_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 3: Ghana", x = "factor", y = "question")
d3_abs_th <- d3_abs %>%
rownames_to_column("subj") %>%
filter(subj %in% c(d3_byq %>% filter(ctry == "thailand") %>% distinct(subj) %>% pull(subj))) %>%
column_to_rownames("subj")
fa.parallel(d3_abs_th)
Parallel analysis suggests that the number of factors = 1 and the number of components = 1
d3_th_efa <- fa(d3_abs, nfactors = 1, rotate = "oblimin")
d3_th_loadings <- d3_th_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d3_th_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 3: Thailand", x = "factor", y = "question")
d3_abs_ch <- d3_abs %>%
rownames_to_column("subj") %>%
filter(subj %in% c(d3_byq %>% filter(ctry == "china") %>% distinct(subj) %>% pull(subj))) %>%
column_to_rownames("subj")
fa.parallel(d3_abs_ch)
the standard deviation is zerothe standard deviation is zerothe standard deviation is zero
Parallel analysis suggests that the number of factors = 2 and the number of components = 2
d3_ch_efa <- fa(d3_abs, nfactors = 2, rotate = "oblimin")
d3_ch_loadings <- d3_ch_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d3_ch_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 3: China", x = "factor", y = "question")
d3_abs_vt <- d3_abs %>%
rownames_to_column("subj") %>%
filter(subj %in% c(d3_byq %>% filter(ctry == "vanuatu") %>% distinct(subj) %>% pull(subj))) %>%
column_to_rownames("subj")
fa.parallel(d3_abs_vt)
Parallel analysis suggests that the number of factors = 2 and the number of components = 2
d3_vt_efa <- fa(d3_abs, nfactors = 2, rotate = "oblimin")
d3_vt_loadings <- d3_vt_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d3_vt_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 3: Vanuatu", x = "factor", y = "question")
d4_abs <- d4_byq %>%
select(p7_subj, contains("_abs_")) %>%
select(-ends_with("cat"), -ends_with("total"), -contains("_check")) %>%
column_to_rownames("p7_subj")
fa.parallel(d4_abs)
Parallel analysis suggests that the number of factors = 4 and the number of components = 3
d4_all_efa <- fa(d4_abs, nfactors = 4, rotate = "oblimin")
d4_all_loadings <- d4_all_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d4_all_loadings %>%
mutate(question = gsub("_abs", "", question),
question = gsub("p7_", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 4: All sites", x = "factor", y = "question")
d4_abs_us <- d4_abs %>%
rownames_to_column("p7_subj") %>%
filter(p7_subj %in% c(d4_byq %>%
filter(p7_ctry == "US") %>%
distinct(p7_subj) %>%
pull(p7_subj))) %>%
column_to_rownames("p7_subj")
fa.parallel(d4_abs_us)
Parallel analysis suggests that the number of factors = 2 and the number of components = 2
There were 45 warnings (use warnings() to see them)
d4_us_efa <- fa(d4_abs_us, nfactors = 2, rotate = "oblimin")
d4_us_loadings <- d4_us_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d4_us_loadings %>%
mutate(question = gsub("_abs", "", question),
question = gsub("p7_", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 4: US", x = "factor", y = "question")
d4_abs_gh <- d4_abs %>%
rownames_to_column("p7_subj") %>%
filter(p7_subj %in% c(d4_byq %>%
filter(p7_ctry == "Ghana") %>%
distinct(p7_subj) %>%
pull(p7_subj))) %>%
column_to_rownames("p7_subj")
fa.parallel(d4_abs_gh)
Parallel analysis suggests that the number of factors = 4 and the number of components = 1
d4_gh_efa <- fa(d4_abs_gh, nfactors = 4, rotate = "oblimin")
d4_gh_loadings <- d4_gh_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d4_gh_loadings %>%
mutate(question = gsub("_abs", "", question),
question = gsub("p7_", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 4: Ghana", x = "factor", y = "question")
d4_abs_th <- d4_abs %>%
rownames_to_column("p7_subj") %>%
filter(p7_subj %in% c(d4_byq %>%
filter(p7_ctry == "Thailand") %>%
distinct(p7_subj) %>%
pull(p7_subj))) %>%
column_to_rownames("p7_subj")
fa.parallel(d4_abs_th)
the standard deviation is zero
Parallel analysis suggests that the number of factors = 1 and the number of components = 1
d4_th_efa <- fa(d4_abs_th, nfactors = 1, rotate = "oblimin")
d4_th_loadings <- d4_th_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d4_th_loadings %>%
mutate(question = gsub("_abs", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 4: Thailand", x = "factor", y = "question")
d4_abs_ch <- d4_abs %>%
rownames_to_column("p7_subj") %>%
filter(p7_subj %in% c(d4_byq %>%
filter(p7_ctry == "China") %>%
distinct(p7_subj) %>%
pull(p7_subj))) %>%
column_to_rownames("p7_subj")
fa.parallel(d4_abs_ch)
the standard deviation is zerothe standard deviation is zerothe standard deviation is zero
Parallel analysis suggests that the number of factors = 1 and the number of components = 1
d4_ch_efa <- fa(d4_abs_ch, nfactors = 1, rotate = "oblimin")
d4_ch_loadings <- d4_ch_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d4_ch_loadings %>%
mutate(question = gsub("_abs", "", question),
question = gsub("p7_", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 4: China", x = "factor", y = "question")
d4_abs_vt <- d4_abs %>%
rownames_to_column("p7_subj") %>%
filter(p7_subj %in% c(d4_byq %>%
filter(p7_ctry == "Vanuatu") %>%
distinct(p7_subj) %>%
pull(p7_subj))) %>%
column_to_rownames("p7_subj")
fa.parallel(d4_abs_vt)
the standard deviation is zero
Parallel analysis suggests that the number of factors = 6 and the number of components = 1
d4_vt_efa <- fa(d4_abs_vt, nfactors = 6, rotate = "oblimin")
d4_vt_loadings <- d4_vt_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d4_vt_loadings %>%
mutate(question = gsub("_abs", "", question),
question = gsub("p7_", "", question)) %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "Study 4: Vanuatu", x = "factor", y = "question")
d_all_abs <- d1_abs %>%
rename_all(~gsub("_abs", "", .)) %>%
rownames_to_column("subject_id") %>%
mutate(study = "s1") %>%
gather(question, response, -c(study, subject_id)) %>%
full_join(d3_abs %>%
rownames_to_column("subject_id") %>%
mutate(study = "s3") %>%
gather(question, response, -c(study, subject_id))) %>%
full_join(d4_abs %>%
rownames_to_column("subject_id") %>%
mutate(study = "s4") %>%
gather(question, response, -c(study, subject_id)) %>%
mutate(question = recode(question,
"p7_abs_child.exp" = "childexp",
"p7_abs_poetic" = "poeticlanguage",
"p7_abs_tv.real" = "forgetsurrounding",
"p7_abs_see.image" = "starepicture",
"p7_abs_mind.world" = "mindenvelopworld",
"p7_abs_clouds" = "cloudshapes",
"p7_abs_vivid.dreams" = "vividdaydream",
"p7_abs_mystic.exp" = "mysticalexp",
"p7_abs_step.outside" = "stepoutsidemyself",
"p7_abs_textures" = "textures",
"p7_abs_too.real" = "doublyreal",
"p7_abs_music.attn" = "caughtupinmusic",
"p7_abs_heavy.body" = "heavybody",
"p7_abs_sense.presc" = "sensepresence",
"p7_abs_fire" = "woodfireimagine",
"p7_abs_nature.art" = "immersednature",
"p7_abs_colors" = "colormeaning",
"p7_abs_thght.wander" = "wanderthoughtstask",
"p7_abs_vivid.past" = "clearpastexp",
"p7_abs_makes.sense" = "meaninglesstoothers",
"p7_abs_become.chctr" = "actinginplay",
"p7_abs_visual.thghts" = "visualthoughts",
"p7_abs_small.things" = "delightsmallthings",
"p7_abs_music.lift" = "organmusic",
"p7_abs_noise.music" = "changenoise",
"p7_abs_scented.mem" = "vividsmellmemories",
"p7_abs_visual.music" = "synesthesiasound",
"p7_abs_before.said" = "predictwords",
"p7_abs_physical.mem" = "physicalmemories",
"p7_abs_voice.sound" = "fascinatingvoice",
"p7_abs_not.physical" = "invisiblepresence",
"p7_abs_thgts.image" = "sponthoughtsimages",
"p7_abs_odor.to.color" = "synesthesiasmell",
"p7_abs_sunset" = "emosunset"))) %>%
unite("study_sub", c(study, subject_id)) %>%
spread(question, response) %>%
column_to_rownames("study_sub")
Joining, by = c("subject_id", "study", "question", "response")
Joining, by = c("subject_id", "study", "question", "response")
fa.parallel(d_all_abs)
Parallel analysis suggests that the number of factors = 6 and the number of components = 4
d_all_all_efa <- fa(d_all_abs, nfactors = 6, rotate = "oblimin")
d_all_all_loadings <- d_all_all_efa$loadings[] %>%
fa.sort() %>%
data.frame() %>%
rownames_to_column("question") %>%
mutate(order = 1:nrow(.)) %>%
gather(factor, loading, -question, -order)
d_all_all_loadings %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
labs(title = "All studies: All sites", x = "factor", y = "question")
d_all_all_scales <- d_all_all_loadings %>%
group_by(factor) %>%
top_n(3, loading) %>%
ungroup()
d_all_all_loadings %>%
ggplot(aes(x = factor, y = reorder(question, desc(order)), fill = loading)) +
geom_tile(color = "black") +
geom_tile(data = d_all_all_scales %>%
mutate(factorlab = recode_factor(factor,
"MR1" = "Synesthesia",
"MR2" = "Aesthetic involvement in nature",
"MR3" = "Altered states of consciousness (a)",
"MR4" = "Imaginative involvement",
"MR5" = "Sensed presence",
"MR6" = "Altered states of consciousness (b)")),
aes(fill = NULL, color = factorlab), alpha = 0, size = 1) +
geom_text(aes(label = format(round(loading, 2), nsmall = 2)), size = 3) +
scale_fill_distiller(palette = "RdYlBu", limits = c(-1, 1)) +
scale_color_brewer(palette = "Set1") +
labs(title = "All studies: All sites", x = "factor", y = "question",
fill = "Factor loading", color = "MODTAS factor") +
theme_minimal()
# reliability
bind_rows(MR1 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s1_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR1") %>%
pull(question)))),
MR2 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s1_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR2") %>%
pull(question)))),
MR3 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s1_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR3") %>%
pull(question)))),
MR4 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s1_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR4") %>%
pull(question)))),
MR5 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s1_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR5") %>%
pull(question)))),
MR6 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s1_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR6") %>%
pull(question)))))
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
d1_abs_subscales <- d1_abs %>%
rownames_to_column("subject_id") %>%
gather(question, response, -subject_id) %>%
mutate(question = gsub("_abs", "", question)) %>%
left_join(d_all_all_scales %>% distinct(question, factor)) %>%
filter(!is.na(factor)) %>%
mutate(factorlab = recode_factor(factor,
"MR1" = "Synesthesia",
"MR2" = "Aesthetic involvement in nature",
"MR3" = "Altered states of consciousness (a)",
"MR4" = "Imaginative involvement",
"MR5" = "Sensed presence",
"MR6" = "Altered states of consciousness (b)")) %>%
group_by(subject_id, factor, factorlab) %>%
summarise(score = mean(response, na.rm = T)) %>%
ungroup() %>%
mutate(subject_id = as.numeric(subject_id)) %>%
left_join(d1 %>% distinct(subject_id, country)) %>%
group_by(country, factor, factorlab) %>%
mutate(score = scale(score)) %>%
ungroup() %>%
select(-country, -factor) %>%
spread(factorlab, score) %>%
mutate_all(as.numeric) %>%
left_join(d1_fortab)
Joining, by = "question"
`summarise()` has grouped output by 'subject_id', 'factor'. You can override using the `.groups` argument.
Joining, by = "subject_id"
Joining, by = "subject_id"
# r104_spev <- lm(`Spiritual Events` ~ `Porosity Vignettes`,
# data = d1_abs_subscales)
r105_spev_MR1 <- lm(`Spiritual Events` ~ Synesthesia,
data = d1_abs_subscales)
r105_spev_MR2 <- lm(`Spiritual Events` ~ `Aesthetic involvement in nature`,
data = d1_abs_subscales)
r105_spev_MR3 <- lm(`Spiritual Events` ~ `Altered states of consciousness (a)`,
data = d1_abs_subscales)
r105_spev_MR4 <- lm(`Spiritual Events` ~ `Imaginative involvement`,
data = d1_abs_subscales)
r105_spev_MR5 <- lm(`Spiritual Events` ~ `Sensed presence`,
data = d1_abs_subscales)
r105_spev_MR6 <- lm(`Spiritual Events` ~ `Altered states of consciousness (b)`,
data = d1_abs_subscales)
r106_spev_MR1 <- lm(`Spiritual Events` ~ `Porosity Vignettes` * Synesthesia,
data = d1_abs_subscales)
r106_spev_MR2 <- lm(`Spiritual Events` ~ `Porosity Vignettes` * `Aesthetic involvement in nature`,
data = d1_abs_subscales)
r106_spev_MR3 <- lm(`Spiritual Events` ~ `Porosity Vignettes` * `Altered states of consciousness (a)`,
data = d1_abs_subscales)
r106_spev_MR4 <- lm(`Spiritual Events` ~ `Porosity Vignettes` * `Imaginative involvement`,
data = d1_abs_subscales)
r106_spev_MR5 <- lm(`Spiritual Events` ~ `Porosity Vignettes` * `Sensed presence`,
data = d1_abs_subscales)
r106_spev_MR6 <- lm(`Spiritual Events` ~ `Porosity Vignettes` * `Altered states of consciousness (b)`,
data = d1_abs_subscales)
# r107_spev <- lm(`Spiritual Events` ~ Country * Site * Religion
# + `Porosity Vignettes` + Country:`Porosity Vignettes`,
# data = d1_abs_subscales)
r108_spev_MR1 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ Synesthesia + Country:Synesthesia,
data = d1_abs_subscales)
r108_spev_MR2 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Aesthetic involvement in nature` + Country:`Aesthetic involvement in nature`,
data = d1_abs_subscales)
r108_spev_MR3 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Altered states of consciousness (a)` + Country:`Altered states of consciousness (a)`,
data = d1_abs_subscales)
r108_spev_MR4 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Imaginative involvement` + Country:`Imaginative involvement`,
data = d1_abs_subscales)
r108_spev_MR5 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Sensed presence` + Country:`Sensed presence`,
data = d1_abs_subscales)
r108_spev_MR6 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Altered states of consciousness (b)` + Country:`Altered states of consciousness (b)`,
data = d1_abs_subscales)
r109_spev_MR1 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ Synesthesia + Country:Synesthesia
+ `Porosity Vignettes`:Synesthesia
+ Country:`Porosity Vignettes`:Synesthesia,
data = d1_abs_subscales)
r109_spev_MR2 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Aesthetic involvement in nature` + Country:`Aesthetic involvement in nature`
+ `Porosity Vignettes`:`Aesthetic involvement in nature`
+ Country:`Porosity Vignettes`:`Aesthetic involvement in nature`,
data = d1_abs_subscales)
r109_spev_MR3 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Altered states of consciousness (a)` + Country:`Altered states of consciousness (a)`
+ `Porosity Vignettes`:`Altered states of consciousness (a)`
+ Country:`Porosity Vignettes`:`Altered states of consciousness (a)`,
data = d1_abs_subscales)
r109_spev_MR4 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Imaginative involvement` + Country:`Imaginative involvement`
+ `Porosity Vignettes`:`Imaginative involvement`
+ Country:`Porosity Vignettes`:`Imaginative involvement`,
data = d1_abs_subscales)
r109_spev_MR5 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Sensed presence` + Country:`Sensed presence`
+ `Porosity Vignettes`:`Sensed presence`
+ Country:`Porosity Vignettes`:`Sensed presence`,
data = d1_abs_subscales)
r109_spev_MR6 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Altered states of consciousness (b)` + Country:`Altered states of consciousness (b)`
+ `Porosity Vignettes`:`Altered states of consciousness (b)`
+ Country:`Porosity Vignettes`:`Altered states of consciousness (b)`,
data = d1_abs_subscales)
r110_spev_MR1 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ Synesthesia + Country:Synesthesia
+ `Porosity Vignettes`:Synesthesia
+ Country:`Porosity Vignettes`:Synesthesia
+ Gender + Age + Education,
data = d1_abs_subscales)
r110_spev_MR2 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Aesthetic involvement in nature` + Country:`Aesthetic involvement in nature`
+ `Porosity Vignettes`:`Aesthetic involvement in nature`
+ Country:`Porosity Vignettes`:`Aesthetic involvement in nature`
+ Gender + Age + Education,
data = d1_abs_subscales)
r110_spev_MR3 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Altered states of consciousness (a)` + Country:`Altered states of consciousness (a)`
+ `Porosity Vignettes`:`Altered states of consciousness (a)`
+ Country:`Porosity Vignettes`:`Altered states of consciousness (a)`
+ Gender + Age + Education,
data = d1_abs_subscales)
r110_spev_MR4 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Imaginative involvement` + Country:`Imaginative involvement`
+ `Porosity Vignettes`:`Imaginative involvement`
+ Country:`Porosity Vignettes`:`Imaginative involvement`
+ Gender + Age + Education,
data = d1_abs_subscales)
r110_spev_MR5 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Sensed presence` + Country:`Sensed presence`
+ `Porosity Vignettes`:`Sensed presence`
+ Country:`Porosity Vignettes`:`Sensed presence`
+ Gender + Age + Education,
data = d1_abs_subscales)
r110_spev_MR6 <- lm(`Spiritual Events` ~ Country * Site * Religion
+ `Porosity Vignettes` + Country:`Porosity Vignettes`
+ `Altered states of consciousness (b)` + Country:`Altered states of consciousness (b)`
+ `Porosity Vignettes`:`Altered states of consciousness (b)`
+ Country:`Porosity Vignettes`:`Altered states of consciousness (b)`
+ Gender + Age + Education,
data = d1_abs_subscales)
table_s20_subscales <- stargazer(
#r104_spev,
r105_spev_MR1, r105_spev_MR2, r105_spev_MR3, r105_spev_MR4, r105_spev_MR5, r105_spev_MR6,
r106_spev_MR1, r106_spev_MR2, r106_spev_MR3, r106_spev_MR4, r106_spev_MR5, r106_spev_MR6,
#r107_spev,
r108_spev_MR1, r108_spev_MR2, r108_spev_MR3, r108_spev_MR4, r108_spev_MR5, r108_spev_MR6,
r109_spev_MR1, r109_spev_MR2, r109_spev_MR3, r109_spev_MR4, r109_spev_MR5, r109_spev_MR6,
r110_spev_MR1, r110_spev_MR2, r110_spev_MR3, r110_spev_MR4, r110_spev_MR5, r110_spev_MR6,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
# order = c("^`Porosity Vignettes`$",
# "^Absorption$",
# "^`Porosity Vignettes`:Absorption$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales),
file = "./stargazer_tables/table_s20_subscales.html")
# htmltools::includeHTML("./stargazer_tables/table_s20_subscales.html")
table_s20_subscales_MR1 <- stargazer(#r104_spev,
r105_spev_MR1, r106_spev_MR1,
#r107_spev,
r108_spev_MR1, r109_spev_MR1, r110_spev_MR1,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^Synesthesia$",
"^`Porosity Vignettes`:Synesthesia$"),
dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales_MR1),
file = "./stargazer_tables/table_s20_subscales_MR1.html")
htmltools::includeHTML("./stargazer_tables/table_s20_subscales_MR1.html")
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.33 (0.23, 0.44) | 0.34 (0.19, 0.48) | 0.31 (0.17, 0.46) | ||
| p = 0.00 | p = 0.00001 | p = 0.00005 | |||
| Synesthesia | 0.14 (0.03, 0.25) | 0.09 (-0.01, 0.20) | 0.18 (0.08, 0.28) | 0.15 (0.04, 0.27) | 0.16 (0.04, 0.27) |
| p = 0.02 | p = 0.09 | p = 0.0005 | p = 0.01 | p = 0.01 | |
| Porosity Vignettes:Synesthesia | -0.02 (-0.13, 0.09) | -0.02 (-0.16, 0.13) | -0.02 (-0.17, 0.12) | ||
| p = 0.75 | p = 0.84 | p = 0.74 | |||
| Country: Gh. | 0.14 (-0.02, 0.31) | 0.02 (-0.20, 0.25) | 0.01 (-0.22, 0.24) | ||
| p = 0.10 | p = 0.85 | p = 0.93 | |||
| Country: Th. | -0.03 (-0.24, 0.18) | -0.09 (-0.32, 0.14) | -0.09 (-0.33, 0.14) | ||
| p = 0.78 | p = 0.45 | p = 0.45 | |||
| Country: Ch. | -0.41 (-0.61, -0.21) | -0.24 (-0.53, 0.06) | -0.24 (-0.53, 0.05) | ||
| p = 0.0001 | p = 0.12 | p = 0.11 | |||
| Country: Va. | 0.79 (0.58, 1.01) | 0.70 (0.47, 0.93) | 0.67 (0.42, 0.92) | ||
| p = 0.00 | p = 0.00 | p = 0.0000004 | |||
| Site: rural | 0.03 (-0.07, 0.12) | 0.02 (-0.07, 0.12) | 0.02 (-0.09, 0.13) | ||
| p = 0.62 | p = 0.64 | p = 0.74 | |||
| Religion: CC | 0.26 (0.16, 0.36) | 0.25 (0.15, 0.35) | 0.25 (0.15, 0.35) | ||
| p = 0.0000005 | p = 0.000003 | p = 0.000003 | |||
| Gender: male | -0.07 (-0.17, 0.03) | ||||
| p = 0.16 | |||||
| Age | -0.08 (-0.19, 0.02) | ||||
| p = 0.13 | |||||
| Education: at least HS | -0.12 (-0.30, 0.06) | ||||
| p = 0.20 | |||||
| Country: Gh. × Site: rural | -0.27 (-0.44, -0.10) | -0.28 (-0.45, -0.11) | -0.24 (-0.42, -0.06) | ||
| p = 0.002 | p = 0.002 | p = 0.01 | |||
| Country: Th. × Site: rural | 0.02 (-0.20, 0.23) | 0.002 (-0.21, 0.22) | 0.01 (-0.20, 0.23) | ||
| p = 0.90 | p = 0.99 | p = 0.91 | |||
| Country: Ch. × Site: rural | 0.43 (0.23, 0.63) | 0.42 (0.23, 0.62) | 0.38 (0.17, 0.60) | ||
| p = 0.00003 | p = 0.00004 | p = 0.001 | |||
| Country: Va. × Site: rural | -0.02 (-0.24, 0.21) | 0.01 (-0.21, 0.23) | 0.001 (-0.22, 0.22) | ||
| p = 0.89 | p = 0.91 | p = 1.00 | |||
| Country: Gh. × Religion: CC | -0.17 (-0.35, 0.01) | -0.11 (-0.30, 0.07) | -0.09 (-0.31, 0.13) | ||
| p = 0.07 | p = 0.22 | p = 0.42 | |||
| Country: Th. × Religion: CC | -0.09 (-0.31, 0.13) | -0.14 (-0.37, 0.08) | -0.15 (-0.38, 0.08) | ||
| p = 0.42 | p = 0.22 | p = 0.21 | |||
| Country: Ch. × Religion: CC | -0.13 (-0.34, 0.07) | -0.13 (-0.33, 0.08) | -0.15 (-0.36, 0.05) | ||
| p = 0.21 | p = 0.23 | p = 0.14 | |||
| Country: Va. × Religion: CC | 0.10 (-0.12, 0.32) | 0.10 (-0.12, 0.33) | 0.11 (-0.12, 0.33) | ||
| p = 0.37 | p = 0.37 | p = 0.35 | |||
| Site: rural × Religion: CC | -0.11 (-0.21, -0.01) | -0.09 (-0.19, 0.01) | -0.12 (-0.22, -0.02) | ||
| p = 0.04 | p = 0.07 | p = 0.03 | |||
| Country: Gh. × Porosity Vignettes | -0.17 (-0.38, 0.03) | -0.16 (-0.37, 0.05) | |||
| p = 0.11 | p = 0.14 | ||||
| Country: Th. × Porosity Vignettes | -0.10 (-0.36, 0.16) | -0.10 (-0.36, 0.16) | |||
| p = 0.44 | p = 0.47 | ||||
| Country: Ch. × Porosity Vignettes | -0.08 (-0.36, 0.20) | -0.05 (-0.33, 0.23) | |||
| p = 0.58 | p = 0.74 | ||||
| Country: Va. × Porosity Vignettes | 0.50 (0.07, 0.93) | 0.45 (0.02, 0.88) | |||
| p = 0.03 | p = 0.05 | ||||
| Country: Gh. × Synesthesia | 0.003 (-0.18, 0.19) | 0.10 (-0.13, 0.33) | 0.12 (-0.11, 0.35) | ||
| p = 0.98 | p = 0.40 | p = 0.30 | |||
| Country: Th. × Synesthesia | 0.09 (-0.11, 0.28) | 0.08 (-0.12, 0.29) | 0.09 (-0.12, 0.30) | ||
| p = 0.38 | p = 0.43 | p = 0.40 | |||
| Country: Ch. × Synesthesia | -0.01 (-0.21, 0.19) | -0.03 (-0.27, 0.22) | -0.03 (-0.27, 0.22) | ||
| p = 0.96 | p = 0.83 | p = 0.84 | |||
| Country: Va. × Synesthesia | -0.09 (-0.31, 0.13) | -0.13 (-0.36, 0.09) | -0.17 (-0.39, 0.06) | ||
| p = 0.44 | p = 0.25 | p = 0.16 | |||
| Country: Gh. × Site: rural × Religion: CC | -0.11 (-0.28, 0.07) | -0.14 (-0.31, 0.03) | -0.16 (-0.33, 0.02) | ||
| p = 0.25 | p = 0.12 | p = 0.09 | |||
| Country: Th. × Site: rural × Religion: CC | 0.30 (0.08, 0.52) | 0.25 (0.04, 0.47) | 0.25 (0.04, 0.47) | ||
| p = 0.01 | p = 0.03 | p = 0.03 | |||
| Country: Ch. × Site: rural × Religion: CC | -0.11 (-0.32, 0.09) | -0.11 (-0.31, 0.09) | -0.11 (-0.30, 0.09) | ||
| p = 0.27 | p = 0.28 | p = 0.30 | |||
| Country: Va. × Site: rural × Religion: CC | -0.05 (-0.28, 0.17) | 0.01 (-0.21, 0.24) | 0.02 (-0.21, 0.24) | ||
| p = 0.64 | p = 0.90 | p = 0.90 | |||
| Country: Gh. × Porosity Vignettes:Synesthesia | -0.08 (-0.29, 0.13) | -0.09 (-0.30, 0.12) | |||
| p = 0.46 | p = 0.40 | ||||
| Country: Th. × Porosity Vignettes:Synesthesia | -0.09 (-0.37, 0.18) | -0.11 (-0.39, 0.16) | |||
| p = 0.51 | p = 0.42 | ||||
| Country: Ch. × Porosity Vignettes:Synesthesia | 0.08 (-0.17, 0.32) | 0.09 (-0.16, 0.33) | |||
| p = 0.54 | p = 0.50 | ||||
| Country: Va. × Porosity Vignettes:Synesthesia | 0.12 (-0.31, 0.55) | 0.13 (-0.30, 0.56) | |||
| p = 0.59 | p = 0.57 | ||||
| Constant | -0.01 (-0.12, 0.10) | -0.01 (-0.12, 0.09) | 0.02 (-0.08, 0.12) | 0.02 (-0.10, 0.14) | 0.07 (-0.07, 0.21) |
| p = 0.83 | p = 0.82 | p = 0.69 | p = 0.72 | p = 0.32 | |
| Observations | 301 | 297 | 301 | 297 | 293 |
| R2 | 0.02 | 0.13 | 0.42 | 0.47 | 0.49 |
| Adjusted R2 | 0.02 | 0.12 | 0.36 | 0.40 | 0.42 |
| Residual Std. Error | 0.98 (df = 299) | 0.93 (df = 293) | 0.79 (df = 276) | 0.77 (df = 262) | 0.76 (df = 255) |
| F Statistic | 6.28** (df = 1; 299) | 14.75*** (df = 3; 293) | 8.17*** (df = 24; 276) | 6.80*** (df = 34; 262) | 6.60*** (df = 37; 255) |
table_s20_subscales_MR2 <- stargazer(#r104_spev,
r105_spev_MR2, r106_spev_MR2,
#r107_spev,
r108_spev_MR2, r109_spev_MR2, r110_spev_MR2,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^`Aesthetic involvement in nature`$",
"^`Porosity Vignettes`:`Aesthetic involvement in nature`$"),
dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales_MR2),
file = "./stargazer_tables/table_s20_subscales_MR2.html")
htmltools::includeHTML("./stargazer_tables/table_s20_subscales_MR2.html")
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.35 (0.24, 0.46) | 0.36 (0.22, 0.50) | 0.34 (0.19, 0.48) | ||
| p = 0.00 | p = 0.000002 | p = 0.00001 | |||
| Aesthetic involvement in nature | 0.08 (-0.04, 0.19) | 0.04 (-0.07, 0.15) | 0.12 (0.02, 0.21) | 0.09 (-0.03, 0.20) | 0.09 (-0.03, 0.20) |
| p = 0.19 | p = 0.48 | p = 0.02 | p = 0.14 | p = 0.14 | |
| Porosity Vignettes:Aesthetic involvement in nature | -0.10 (-0.21, 0.01) | -0.20 (-0.36, -0.05) | -0.23 (-0.39, -0.07) | ||
| p = 0.07 | p = 0.02 | p = 0.005 | |||
| Country: Gh. | 0.14 (-0.04, 0.31) | 0.07 (-0.16, 0.29) | 0.05 (-0.19, 0.28) | ||
| p = 0.13 | p = 0.57 | p = 0.70 | |||
| Country: Th. | -0.03 (-0.25, 0.18) | -0.12 (-0.35, 0.10) | -0.12 (-0.35, 0.12) | ||
| p = 0.76 | p = 0.30 | p = 0.33 | |||
| Country: Ch. | -0.40 (-0.60, -0.20) | -0.18 (-0.43, 0.08) | -0.17 (-0.43, 0.08) | ||
| p = 0.0002 | p = 0.18 | p = 0.19 | |||
| Country: Va. | 0.80 (0.58, 1.01) | 0.67 (0.45, 0.89) | 0.61 (0.36, 0.86) | ||
| p = 0.00 | p = 0.00 | p = 0.000003 | |||
| Site: rural | 0.03 (-0.07, 0.13) | 0.03 (-0.07, 0.12) | 0.01 (-0.10, 0.13) | ||
| p = 0.52 | p = 0.57 | p = 0.83 | |||
| Religion: CC | 0.24 (0.14, 0.34) | 0.23 (0.13, 0.33) | 0.23 (0.14, 0.33) | ||
| p = 0.000003 | p = 0.00001 | p = 0.000005 | |||
| Gender: male | -0.05 (-0.14, 0.04) | ||||
| p = 0.30 | |||||
| Age | -0.09 (-0.19, 0.02) | ||||
| p = 0.12 | |||||
| Education: at least HS | -0.14 (-0.33, 0.04) | ||||
| p = 0.12 | |||||
| Country: Gh. × Site: rural | -0.27 (-0.44, -0.10) | -0.29 (-0.45, -0.12) | -0.23 (-0.41, -0.06) | ||
| p = 0.003 | p = 0.002 | p = 0.01 | |||
| Country: Th. × Site: rural | 0.02 (-0.21, 0.24) | 0.02 (-0.20, 0.24) | 0.04 (-0.18, 0.25) | ||
| p = 0.90 | p = 0.86 | p = 0.75 | |||
| Country: Ch. × Site: rural | 0.44 (0.24, 0.64) | 0.43 (0.23, 0.63) | 0.38 (0.16, 0.59) | ||
| p = 0.00003 | p = 0.00003 | p = 0.001 | |||
| Country: Va. × Site: rural | -0.0001 (-0.22, 0.22) | 0.01 (-0.20, 0.22) | -0.02 (-0.23, 0.19) | ||
| p = 1.00 | p = 0.95 | p = 0.86 | |||
| Country: Gh. × Religion: CC | -0.18 (-0.36, -0.01) | -0.12 (-0.29, 0.05) | -0.09 (-0.29, 0.12) | ||
| p = 0.04 | p = 0.17 | p = 0.40 | |||
| Country: Th. × Religion: CC | -0.08 (-0.30, 0.14) | -0.12 (-0.34, 0.10) | -0.13 (-0.36, 0.10) | ||
| p = 0.50 | p = 0.28 | p = 0.27 | |||
| Country: Ch. × Religion: CC | -0.16 (-0.36, 0.04) | -0.12 (-0.31, 0.07) | -0.15 (-0.35, 0.04) | ||
| p = 0.12 | p = 0.22 | p = 0.13 | |||
| Country: Va. × Religion: CC | 0.11 (-0.10, 0.33) | 0.08 (-0.13, 0.29) | 0.09 (-0.12, 0.30) | ||
| p = 0.31 | p = 0.45 | p = 0.41 | |||
| Site: rural × Religion: CC | -0.12 (-0.21, -0.02) | -0.10 (-0.19, 0.001) | -0.12 (-0.22, -0.02) | ||
| p = 0.03 | p = 0.06 | p = 0.02 | |||
| Country: Gh. × Porosity Vignettes | -0.24 (-0.45, -0.03) | -0.23 (-0.44, -0.02) | |||
| p = 0.03 | p = 0.04 | ||||
| Country: Th. × Porosity Vignettes | -0.08 (-0.34, 0.18) | -0.08 (-0.34, 0.18) | |||
| p = 0.54 | p = 0.56 | ||||
| Country: Ch. × Porosity Vignettes | -0.06 (-0.32, 0.19) | -0.03 (-0.29, 0.23) | |||
| p = 0.64 | p = 0.83 | ||||
| Country: Va. × Porosity Vignettes | 0.56 (0.14, 0.98) | 0.50 (0.08, 0.92) | |||
| p = 0.01 | p = 0.03 | ||||
| Country: Gh. × Aesthetic involvement in nature | 0.04 (-0.13, 0.22) | 0.17 (-0.05, 0.38) | 0.18 (-0.04, 0.39) | ||
| p = 0.63 | p = 0.13 | p = 0.11 | |||
| Country: Th. × Aesthetic involvement in nature | 0.12 (-0.08, 0.32) | 0.13 (-0.08, 0.34) | 0.13 (-0.08, 0.34) | ||
| p = 0.26 | p = 0.23 | p = 0.24 | |||
| Country: Ch. × Aesthetic involvement in nature | 0.04 (-0.15, 0.23) | -0.11 (-0.41, 0.18) | -0.15 (-0.45, 0.14) | ||
| p = 0.70 | p = 0.47 | p = 0.32 | |||
| Country: Va. × Aesthetic involvement in nature | -0.10 (-0.30, 0.11) | -0.01 (-0.22, 0.21) | 0.02 (-0.19, 0.24) | ||
| p = 0.37 | p = 0.95 | p = 0.84 | |||
| Country: Gh. × Site: rural × Religion: CC | -0.07 (-0.24, 0.10) | -0.11 (-0.28, 0.05) | -0.13 (-0.30, 0.05) | ||
| p = 0.42 | p = 0.19 | p = 0.16 | |||
| Country: Th. × Site: rural × Religion: CC | 0.26 (0.05, 0.48) | 0.20 (-0.01, 0.41) | 0.19 (-0.03, 0.40) | ||
| p = 0.02 | p = 0.07 | p = 0.10 | |||
| Country: Ch. × Site: rural × Religion: CC | -0.13 (-0.33, 0.07) | -0.11 (-0.31, 0.08) | -0.11 (-0.30, 0.08) | ||
| p = 0.22 | p = 0.25 | p = 0.26 | |||
| Country: Va. × Site: rural × Religion: CC | -0.08 (-0.30, 0.14) | 0.01 (-0.21, 0.22) | 0.02 (-0.20, 0.23) | ||
| p = 0.46 | p = 0.95 | p = 0.87 | |||
| Country: Gh. × Porosity Vignettes:Aesthetic involvement in nature | 0.10 (-0.11, 0.31) | 0.10 (-0.11, 0.30) | |||
| p = 0.36 | p = 0.36 | ||||
| Country: Th. × Porosity Vignettes:Aesthetic involvement in nature | 0.06 (-0.21, 0.34) | 0.08 (-0.20, 0.36) | |||
| p = 0.65 | p = 0.57 | ||||
| Country: Ch. × Porosity Vignettes:Aesthetic involvement in nature | 0.05 (-0.24, 0.34) | 0.04 (-0.25, 0.33) | |||
| p = 0.74 | p = 0.77 | ||||
| Country: Va. × Porosity Vignettes:Aesthetic involvement in nature | -0.23 (-0.71, 0.24) | -0.28 (-0.76, 0.19) | |||
| p = 0.35 | p = 0.25 | ||||
| Constant | -0.01 (-0.12, 0.10) | -0.01 (-0.11, 0.10) | 0.02 (-0.08, 0.12) | 0.04 (-0.07, 0.16) | 0.10 (-0.03, 0.24) |
| p = 0.83 | p = 0.92 | p = 0.66 | p = 0.48 | p = 0.15 | |
| Observations | 301 | 297 | 301 | 297 | 293 |
| R2 | 0.01 | 0.13 | 0.40 | 0.48 | 0.50 |
| Adjusted R2 | 0.002 | 0.13 | 0.35 | 0.41 | 0.42 |
| Residual Std. Error | 0.98 (df = 299) | 0.93 (df = 293) | 0.79 (df = 276) | 0.76 (df = 262) | 0.75 (df = 255) |
| F Statistic | 1.73 (df = 1; 299) | 15.22*** (df = 3; 293) | 7.76*** (df = 24; 276) | 7.01*** (df = 34; 262) | 6.77*** (df = 37; 255) |
table_s20_subscales_MR3 <- stargazer(#r104_spev,
r105_spev_MR3, r106_spev_MR3,
#r107_spev,
r108_spev_MR3, r109_spev_MR3, r110_spev_MR3,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Porosity Vignettes`:`Altered states of consciousness \\(a\\)`$"),
dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales_MR3),
file = "./stargazer_tables/table_s20_subscales_MR3.html")
htmltools::includeHTML("./stargazer_tables/table_s20_subscales_MR3.html")
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.33 (0.23, 0.44) | 0.36 (0.22, 0.50) | 0.33 (0.19, 0.47) | ||
| p = 0.00 | p = 0.000002 | p = 0.00002 | |||
| Altered states of consciousness (a) | 0.14 (0.03, 0.26) | 0.10 (-0.003, 0.21) | 0.14 (0.04, 0.23) | 0.11 (-0.01, 0.22) | 0.13 (0.01, 0.24) |
| p = 0.02 | p = 0.06 | p = 0.01 | p = 0.08 | p = 0.04 | |
| Porosity Vignettes:Altered states of consciousness (a) | -0.04 (-0.15, 0.07) | 0.03 (-0.12, 0.17) | 0.01 (-0.14, 0.15) | ||
| p = 0.49 | p = 0.72 | p = 0.94 | |||
| Country: Gh. | 0.14 (-0.03, 0.31) | 0.09 (-0.14, 0.32) | 0.10 (-0.14, 0.33) | ||
| p = 0.11 | p = 0.45 | p = 0.43 | |||
| Country: Th. | -0.04 (-0.25, 0.18) | -0.15 (-0.37, 0.07) | -0.14 (-0.37, 0.09) | ||
| p = 0.73 | p = 0.20 | p = 0.23 | |||
| Country: Ch. | -0.40 (-0.60, -0.21) | -0.20 (-0.46, 0.06) | -0.22 (-0.47, 0.04) | ||
| p = 0.0001 | p = 0.14 | p = 0.11 | |||
| Country: Va. | 0.80 (0.59, 1.01) | 0.69 (0.47, 0.91) | 0.62 (0.37, 0.86) | ||
| p = 0.00 | p = 0.00 | p = 0.000002 | |||
| Site: rural | 0.06 (-0.04, 0.15) | 0.05 (-0.05, 0.15) | 0.03 (-0.09, 0.14) | ||
| p = 0.28 | p = 0.31 | p = 0.67 | |||
| Religion: CC | 0.23 (0.13, 0.32) | 0.22 (0.12, 0.32) | 0.23 (0.13, 0.32) | ||
| p = 0.00001 | p = 0.00002 | p = 0.00002 | |||
| Gender: male | -0.06 (-0.16, 0.03) | ||||
| p = 0.19 | |||||
| Age | -0.07 (-0.18, 0.03) | ||||
| p = 0.18 | |||||
| Education: at least HS | -0.17 (-0.35, 0.01) | ||||
| p = 0.07 | |||||
| Country: Gh. × Site: rural | -0.21 (-0.39, -0.03) | -0.24 (-0.42, -0.07) | -0.19 (-0.38, -0.01) | ||
| p = 0.03 | p = 0.01 | p = 0.05 | |||
| Country: Th. × Site: rural | -0.02 (-0.23, 0.20) | -0.01 (-0.23, 0.21) | 0.01 (-0.21, 0.22) | ||
| p = 0.89 | p = 0.91 | p = 0.97 | |||
| Country: Ch. × Site: rural | 0.44 (0.24, 0.65) | 0.45 (0.25, 0.64) | 0.38 (0.17, 0.59) | ||
| p = 0.00003 | p = 0.00002 | p = 0.0005 | |||
| Country: Va. × Site: rural | -0.005 (-0.22, 0.21) | 0.02 (-0.19, 0.23) | -0.01 (-0.22, 0.20) | ||
| p = 0.97 | p = 0.88 | p = 0.92 | |||
| Country: Gh. × Religion: CC | -0.22 (-0.39, -0.05) | -0.18 (-0.35, -0.01) | -0.12 (-0.32, 0.08) | ||
| p = 0.02 | p = 0.05 | p = 0.24 | |||
| Country: Th. × Religion: CC | -0.06 (-0.28, 0.15) | -0.10 (-0.32, 0.13) | -0.13 (-0.36, 0.10) | ||
| p = 0.56 | p = 0.40 | p = 0.28 | |||
| Country: Ch. × Religion: CC | -0.13 (-0.32, 0.07) | -0.10 (-0.29, 0.09) | -0.13 (-0.32, 0.06) | ||
| p = 0.21 | p = 0.32 | p = 0.19 | |||
| Country: Va. × Religion: CC | 0.11 (-0.11, 0.33) | 0.10 (-0.11, 0.31) | 0.10 (-0.11, 0.32) | ||
| p = 0.33 | p = 0.36 | p = 0.34 | |||
| Site: rural × Religion: CC | -0.12 (-0.22, -0.02) | -0.10 (-0.19, -0.001) | -0.12 (-0.22, -0.03) | ||
| p = 0.02 | p = 0.05 | p = 0.02 | |||
| Country: Gh. × Porosity Vignettes | -0.29 (-0.50, -0.08) | -0.29 (-0.50, -0.08) | |||
| p = 0.01 | p = 0.01 | ||||
| Country: Th. × Porosity Vignettes | -0.07 (-0.32, 0.18) | -0.06 (-0.31, 0.20) | |||
| p = 0.58 | p = 0.67 | ||||
| Country: Ch. × Porosity Vignettes | -0.05 (-0.31, 0.21) | 0.001 (-0.26, 0.26) | |||
| p = 0.72 | p = 1.00 | ||||
| Country: Va. × Porosity Vignettes | 0.58 (0.15, 1.00) | 0.49 (0.06, 0.92) | |||
| p = 0.01 | p = 0.03 | ||||
| Country: Gh. × Altered states of consciousness (a) | 0.13 (-0.05, 0.31) | 0.18 (-0.02, 0.39) | 0.21 (0.01, 0.42) | ||
| p = 0.15 | p = 0.09 | p = 0.05 | |||
| Country: Th. × Altered states of consciousness (a) | 0.08 (-0.11, 0.28) | 0.12 (-0.10, 0.33) | 0.10 (-0.11, 0.32) | ||
| p = 0.40 | p = 0.29 | p = 0.36 | |||
| Country: Ch. × Altered states of consciousness (a) | 0.08 (-0.11, 0.28) | -0.01 (-0.30, 0.28) | -0.02 (-0.31, 0.27) | ||
| p = 0.39 | p = 0.95 | p = 0.91 | |||
| Country: Va. × Altered states of consciousness (a) | -0.26 (-0.47, -0.06) | -0.22 (-0.43, -0.01) | -0.23 (-0.44, -0.02) | ||
| p = 0.02 | p = 0.05 | p = 0.04 | |||
| Country: Gh. × Site: rural × Religion: CC | -0.07 (-0.24, 0.09) | -0.12 (-0.28, 0.05) | -0.13 (-0.30, 0.04) | ||
| p = 0.40 | p = 0.16 | p = 0.13 | |||
| Country: Th. × Site: rural × Religion: CC | 0.29 (0.07, 0.50) | 0.23 (0.03, 0.44) | 0.22 (0.01, 0.43) | ||
| p = 0.01 | p = 0.03 | p = 0.05 | |||
| Country: Ch. × Site: rural × Religion: CC | -0.14 (-0.33, 0.06) | -0.13 (-0.33, 0.06) | -0.13 (-0.32, 0.06) | ||
| p = 0.17 | p = 0.17 | p = 0.19 | |||
| Country: Va. × Site: rural × Religion: CC | -0.09 (-0.31, 0.12) | 0.003 (-0.21, 0.22) | 0.01 (-0.20, 0.23) | ||
| p = 0.42 | p = 0.98 | p = 0.91 | |||
| Country: Gh. × Porosity Vignettes:Altered states of consciousness (a) | -0.13 (-0.33, 0.07) | -0.17 (-0.37, 0.03) | |||
| p = 0.22 | p = 0.10 | ||||
| Country: Th. × Porosity Vignettes:Altered states of consciousness (a) | -0.003 (-0.31, 0.30) | -0.01 (-0.32, 0.29) | |||
| p = 0.99 | p = 0.94 | ||||
| Country: Ch. × Porosity Vignettes:Altered states of consciousness (a) | -0.14 (-0.42, 0.15) | -0.10 (-0.38, 0.18) | |||
| p = 0.36 | p = 0.48 | ||||
| Country: Va. × Porosity Vignettes:Altered states of consciousness (a) | 0.37 (-0.02, 0.76) | 0.36 (-0.03, 0.74) | |||
| p = 0.07 | p = 0.08 | ||||
| Constant | -0.01 (-0.12, 0.10) | -0.01 (-0.12, 0.10) | 0.02 (-0.07, 0.12) | 0.06 (-0.05, 0.17) | 0.13 (-0.003, 0.27) |
| p = 0.84 | p = 0.86 | p = 0.65 | p = 0.31 | p = 0.06 | |
| Observations | 301 | 297 | 301 | 297 | 293 |
| R2 | 0.02 | 0.14 | 0.42 | 0.48 | 0.50 |
| Adjusted R2 | 0.02 | 0.13 | 0.37 | 0.42 | 0.43 |
| Residual Std. Error | 0.98 (df = 299) | 0.93 (df = 293) | 0.78 (df = 276) | 0.76 (df = 262) | 0.75 (df = 255) |
| F Statistic | 6.43** (df = 1; 299) | 15.32*** (df = 3; 293) | 8.35*** (df = 24; 276) | 7.19*** (df = 34; 262) | 7.00*** (df = 37; 255) |
table_s20_subscales_MR4 <- stargazer(#r104_spev,
r105_spev_MR4, r106_spev_MR4,
#r107_spev,
r108_spev_MR4, r109_spev_MR4, r110_spev_MR4,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^`Imaginative involvement`$",
"^`Porosity Vignettes`:`Imaginative involvement`$"),
dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales_MR4),
file = "./stargazer_tables/table_s20_subscales_MR4.html")
htmltools::includeHTML("./stargazer_tables/table_s20_subscales_MR4.html")
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.34 (0.23, 0.44) | 0.32 (0.17, 0.47) | 0.30 (0.15, 0.45) | ||
| p = 0.00 | p = 0.0001 | p = 0.0002 | |||
| Imaginative involvement | 0.09 (-0.02, 0.20) | 0.05 (-0.06, 0.16) | 0.15 (0.06, 0.25) | 0.15 (0.03, 0.28) | 0.14 (0.02, 0.27) |
| p = 0.12 | p = 0.35 | p = 0.002 | p = 0.02 | p = 0.03 | |
| Porosity Vignettes:Imaginative involvement | 0.02 (-0.09, 0.13) | 0.02 (-0.12, 0.15) | -0.003 (-0.14, 0.14) | ||
| p = 0.75 | p = 0.83 | p = 0.98 | |||
| Country: Gh. | 0.14 (-0.03, 0.31) | 0.08 (-0.15, 0.31) | 0.06 (-0.18, 0.30) | ||
| p = 0.10 | p = 0.52 | p = 0.65 | |||
| Country: Th. | -0.06 (-0.27, 0.15) | -0.14 (-0.37, 0.09) | -0.15 (-0.39, 0.09) | ||
| p = 0.59 | p = 0.23 | p = 0.22 | |||
| Country: Ch. | -0.40 (-0.59, -0.20) | -0.27 (-0.58, 0.05) | -0.25 (-0.56, 0.06) | ||
| p = 0.0001 | p = 0.10 | p = 0.12 | |||
| Country: Va. | 0.81 (0.59, 1.02) | 0.72 (0.49, 0.95) | 0.70 (0.44, 0.95) | ||
| p = 0.00 | p = 0.00 | p = 0.0000002 | |||
| Site: rural | 0.03 (-0.07, 0.13) | 0.03 (-0.07, 0.12) | 0.02 (-0.09, 0.14) | ||
| p = 0.52 | p = 0.60 | p = 0.69 | |||
| Religion: CC | 0.23 (0.14, 0.33) | 0.22 (0.12, 0.32) | 0.22 (0.13, 0.32) | ||
| p = 0.000005 | p = 0.00002 | p = 0.00002 | |||
| Gender: male | -0.07 (-0.17, 0.02) | ||||
| p = 0.13 | |||||
| Age | -0.08 (-0.19, 0.03) | ||||
| p = 0.18 | |||||
| Education: at least HS | -0.10 (-0.28, 0.08) | ||||
| p = 0.27 | |||||
| Country: Gh. × Site: rural | -0.24 (-0.42, -0.07) | -0.25 (-0.42, -0.08) | -0.23 (-0.41, -0.05) | ||
| p = 0.01 | p = 0.005 | p = 0.02 | |||
| Country: Th. × Site: rural | -0.05 (-0.26, 0.16) | -0.05 (-0.26, 0.16) | -0.03 (-0.25, 0.18) | ||
| p = 0.65 | p = 0.66 | p = 0.77 | |||
| Country: Ch. × Site: rural | 0.45 (0.25, 0.65) | 0.45 (0.25, 0.64) | 0.41 (0.20, 0.63) | ||
| p = 0.00002 | p = 0.00002 | p = 0.0003 | |||
| Country: Va. × Site: rural | 0.03 (-0.19, 0.24) | 0.02 (-0.20, 0.24) | 0.02 (-0.20, 0.24) | ||
| p = 0.81 | p = 0.83 | p = 0.87 | |||
| Country: Gh. × Religion: CC | -0.23 (-0.40, -0.06) | -0.18 (-0.35, -0.004) | -0.16 (-0.37, 0.05) | ||
| p = 0.01 | p = 0.05 | p = 0.14 | |||
| Country: Th. × Religion: CC | -0.12 (-0.33, 0.09) | -0.15 (-0.37, 0.06) | -0.15 (-0.38, 0.08) | ||
| p = 0.28 | p = 0.17 | p = 0.21 | |||
| Country: Ch. × Religion: CC | -0.13 (-0.33, 0.06) | -0.12 (-0.32, 0.08) | -0.15 (-0.35, 0.05) | ||
| p = 0.19 | p = 0.24 | p = 0.15 | |||
| Country: Va. × Religion: CC | 0.17 (-0.05, 0.38) | 0.14 (-0.07, 0.36) | 0.15 (-0.07, 0.37) | ||
| p = 0.14 | p = 0.20 | p = 0.19 | |||
| Site: rural × Religion: CC | -0.12 (-0.22, -0.02) | -0.10 (-0.20, -0.01) | -0.12 (-0.22, -0.02) | ||
| p = 0.02 | p = 0.05 | p = 0.02 | |||
| Country: Gh. × Porosity Vignettes | -0.22 (-0.44, 0.0003) | -0.18 (-0.41, 0.04) | |||
| p = 0.06 | p = 0.11 | ||||
| Country: Th. × Porosity Vignettes | -0.03 (-0.29, 0.23) | -0.03 (-0.30, 0.23) | |||
| p = 0.81 | p = 0.80 | ||||
| Country: Ch. × Porosity Vignettes | -0.10 (-0.40, 0.21) | -0.06 (-0.37, 0.25) | |||
| p = 0.54 | p = 0.73 | ||||
| Country: Va. × Porosity Vignettes | 0.45 (0.01, 0.89) | 0.39 (-0.06, 0.83) | |||
| p = 0.05 | p = 0.10 | ||||
| Country: Gh. × Imaginative involvement | 0.07 (-0.12, 0.25) | 0.09 (-0.14, 0.32) | 0.08 (-0.16, 0.31) | ||
| p = 0.49 | p = 0.46 | p = 0.53 | |||
| Country: Th. × Imaginative involvement | -0.10 (-0.29, 0.09) | -0.09 (-0.31, 0.13) | -0.08 (-0.30, 0.14) | ||
| p = 0.30 | p = 0.43 | p = 0.47 | |||
| Country: Ch. × Imaginative involvement | 0.04 (-0.16, 0.23) | 0.07 (-0.28, 0.41) | 0.04 (-0.31, 0.38) | ||
| p = 0.73 | p = 0.72 | p = 0.83 | |||
| Country: Va. × Imaginative involvement | 0.10 (-0.11, 0.30) | 0.03 (-0.20, 0.26) | 0.05 (-0.18, 0.28) | ||
| p = 0.36 | p = 0.78 | p = 0.65 | |||
| Country: Gh. × Site: rural × Religion: CC | -0.13 (-0.31, 0.05) | -0.18 (-0.36, 0.003) | -0.17 (-0.35, 0.01) | ||
| p = 0.18 | p = 0.06 | p = 0.07 | |||
| Country: Th. × Site: rural × Religion: CC | 0.29 (0.07, 0.50) | 0.24 (0.03, 0.46) | 0.24 (0.02, 0.46) | ||
| p = 0.01 | p = 0.03 | p = 0.04 | |||
| Country: Ch. × Site: rural × Religion: CC | -0.12 (-0.32, 0.08) | -0.11 (-0.30, 0.09) | -0.11 (-0.31, 0.08) | ||
| p = 0.23 | p = 0.29 | p = 0.27 | |||
| Country: Va. × Site: rural × Religion: CC | -0.05 (-0.27, 0.16) | 0.02 (-0.20, 0.24) | 0.02 (-0.20, 0.24) | ||
| p = 0.63 | p = 0.84 | p = 0.84 | |||
| Country: Gh. × Porosity Vignettes:Imaginative involvement | -0.04 (-0.25, 0.18) | -0.08 (-0.29, 0.14) | |||
| p = 0.75 | p = 0.49 | ||||
| Country: Th. × Porosity Vignettes:Imaginative involvement | 0.01 (-0.23, 0.25) | -0.02 (-0.27, 0.22) | |||
| p = 0.96 | p = 0.85 | ||||
| Country: Ch. × Porosity Vignettes:Imaginative involvement | 0.09 (-0.23, 0.40) | 0.08 (-0.23, 0.40) | |||
| p = 0.60 | p = 0.62 | ||||
| Country: Va. × Porosity Vignettes:Imaginative involvement | -0.04 (-0.41, 0.32) | -0.001 (-0.36, 0.36) | |||
| p = 0.82 | p = 1.00 | ||||
| Constant | -0.01 (-0.12, 0.10) | -0.02 (-0.12, 0.09) | 0.02 (-0.08, 0.11) | 0.02 (-0.10, 0.15) | 0.07 (-0.07, 0.21) |
| p = 0.82 | p = 0.76 | p = 0.75 | p = 0.70 | p = 0.36 | |
| Observations | 301 | 297 | 301 | 297 | 293 |
| R2 | 0.01 | 0.13 | 0.41 | 0.46 | 0.48 |
| Adjusted R2 | 0.005 | 0.12 | 0.36 | 0.39 | 0.40 |
| Residual Std. Error | 0.98 (df = 299) | 0.93 (df = 293) | 0.79 (df = 276) | 0.77 (df = 262) | 0.77 (df = 255) |
| F Statistic | 2.49 (df = 1; 299) | 13.98*** (df = 3; 293) | 8.00*** (df = 24; 276) | 6.64*** (df = 34; 262) | 6.30*** (df = 37; 255) |
table_s20_subscales_MR5 <- stargazer(#r104_spev,
r105_spev_MR5, r106_spev_MR5,
#r107_spev,
r108_spev_MR5, r109_spev_MR5, r110_spev_MR5,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^`Sensed presence`$",
"^`Porosity Vignettes`:`Sensed presence`$"),
dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales_MR5),
file = "./stargazer_tables/table_s20_subscales_MR5.html")
htmltools::includeHTML("./stargazer_tables/table_s20_subscales_MR5.html")
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.32 (0.21, 0.42) | 0.33 (0.19, 0.47) | 0.31 (0.17, 0.45) | ||
| p = 0.00 | p = 0.00001 | p = 0.00002 | |||
| Sensed presence | 0.26 (0.15, 0.37) | 0.22 (0.11, 0.32) | 0.27 (0.17, 0.36) | 0.23 (0.13, 0.34) | 0.23 (0.12, 0.34) |
| p = 0.00001 | p = 0.0001 | p = 0.00000005 | p = 0.00003 | p = 0.00005 | |
| Porosity Vignettes:Sensed presence | -0.0003 (-0.11, 0.11) | -0.11 (-0.25, 0.03) | -0.14 (-0.28, 0.002) | ||
| p = 1.00 | p = 0.12 | p = 0.06 | |||
| Country: Gh. | 0.16 (-0.01, 0.32) | 0.04 (-0.18, 0.26) | 0.02 (-0.20, 0.25) | ||
| p = 0.07 | p = 0.71 | p = 0.85 | |||
| Country: Th. | -0.07 (-0.27, 0.14) | -0.15 (-0.37, 0.06) | -0.14 (-0.36, 0.08) | ||
| p = 0.52 | p = 0.17 | p = 0.23 | |||
| Country: Ch. | -0.39 (-0.58, -0.20) | -0.18 (-0.44, 0.08) | -0.18 (-0.44, 0.08) | ||
| p = 0.0001 | p = 0.19 | p = 0.18 | |||
| Country: Va. | 0.79 (0.58, 0.99) | 0.70 (0.48, 0.92) | 0.65 (0.41, 0.89) | ||
| p = 0.00 | p = 0.00 | p = 0.0000002 | |||
| Site: rural | -0.01 (-0.10, 0.09) | -0.003 (-0.10, 0.09) | -0.01 (-0.12, 0.10) | ||
| p = 0.92 | p = 0.96 | p = 0.86 | |||
| Religion: CC | 0.23 (0.14, 0.33) | 0.21 (0.12, 0.31) | 0.21 (0.12, 0.31) | ||
| p = 0.000004 | p = 0.00002 | p = 0.00002 | |||
| Gender: male | -0.02 (-0.11, 0.07) | ||||
| p = 0.62 | |||||
| Age | -0.10 (-0.20, 0.01) | ||||
| p = 0.09 | |||||
| Education: at least HS | -0.13 (-0.30, 0.04) | ||||
| p = 0.15 | |||||
| Country: Gh. × Site: rural | -0.19 (-0.35, -0.02) | -0.21 (-0.38, -0.04) | -0.16 (-0.34, 0.02) | ||
| p = 0.03 | p = 0.02 | p = 0.09 | |||
| Country: Th. × Site: rural | -0.02 (-0.23, 0.18) | -0.02 (-0.22, 0.19) | -0.01 (-0.22, 0.19) | ||
| p = 0.84 | p = 0.86 | p = 0.90 | |||
| Country: Ch. × Site: rural | 0.41 (0.22, 0.61) | 0.45 (0.26, 0.64) | 0.42 (0.21, 0.63) | ||
| p = 0.0001 | p = 0.00001 | p = 0.0002 | |||
| Country: Va. × Site: rural | -0.07 (-0.28, 0.15) | -0.07 (-0.29, 0.14) | -0.11 (-0.32, 0.11) | ||
| p = 0.55 | p = 0.50 | p = 0.33 | |||
| Country: Gh. × Religion: CC | -0.14 (-0.31, 0.02) | -0.08 (-0.25, 0.08) | -0.06 (-0.26, 0.14) | ||
| p = 0.10 | p = 0.32 | p = 0.55 | |||
| Country: Th. × Religion: CC | -0.14 (-0.35, 0.06) | -0.18 (-0.38, 0.03) | -0.18 (-0.40, 0.04) | ||
| p = 0.17 | p = 0.10 | p = 0.11 | |||
| Country: Ch. × Religion: CC | -0.12 (-0.32, 0.08) | -0.11 (-0.31, 0.09) | -0.15 (-0.35, 0.05) | ||
| p = 0.25 | p = 0.29 | p = 0.16 | |||
| Country: Va. × Religion: CC | 0.09 (-0.12, 0.30) | 0.06 (-0.15, 0.27) | 0.08 (-0.13, 0.29) | ||
| p = 0.39 | p = 0.57 | p = 0.47 | |||
| Site: rural × Religion: CC | -0.15 (-0.25, -0.06) | -0.14 (-0.23, -0.04) | -0.16 (-0.25, -0.06) | ||
| p = 0.002 | p = 0.01 | p = 0.002 | |||
| Country: Gh. × Porosity Vignettes | -0.21 (-0.42, -0.01) | -0.21 (-0.41, -0.005) | |||
| p = 0.05 | p = 0.05 | ||||
| Country: Th. × Porosity Vignettes | -0.08 (-0.33, 0.17) | -0.06 (-0.31, 0.19) | |||
| p = 0.55 | p = 0.66 | ||||
| Country: Ch. × Porosity Vignettes | -0.003 (-0.26, 0.25) | 0.02 (-0.24, 0.28) | |||
| p = 0.99 | p = 0.90 | ||||
| Country: Va. × Porosity Vignettes | 0.40 (-0.02, 0.81) | 0.35 (-0.07, 0.76) | |||
| p = 0.07 | p = 0.11 | ||||
| Country: Gh. × Sensed presence | 0.04 (-0.14, 0.22) | 0.11 (-0.10, 0.31) | 0.14 (-0.06, 0.34) | ||
| p = 0.64 | p = 0.32 | p = 0.18 | |||
| Country: Th. × Sensed presence | 0.12 (-0.07, 0.31) | 0.16 (-0.04, 0.35) | 0.15 (-0.05, 0.35) | ||
| p = 0.21 | p = 0.13 | p = 0.15 | |||
| Country: Ch. × Sensed presence | -0.17 (-0.37, 0.03) | -0.24 (-0.48, 0.004) | -0.26 (-0.50, -0.02) | ||
| p = 0.09 | p = 0.06 | p = 0.04 | |||
| Country: Va. × Sensed presence | 0.12 (-0.08, 0.32) | 0.09 (-0.12, 0.30) | 0.08 (-0.13, 0.29) | ||
| p = 0.25 | p = 0.40 | p = 0.44 | |||
| Country: Gh. × Site: rural × Religion: CC | -0.13 (-0.31, 0.04) | -0.18 (-0.35, -0.01) | -0.21 (-0.39, -0.04) | ||
| p = 0.14 | p = 0.05 | p = 0.02 | |||
| Country: Th. × Site: rural × Religion: CC | 0.19 (-0.02, 0.41) | 0.16 (-0.05, 0.36) | 0.15 (-0.06, 0.36) | ||
| p = 0.08 | p = 0.15 | p = 0.17 | |||
| Country: Ch. × Site: rural × Religion: CC | -0.10 (-0.29, 0.09) | -0.09 (-0.28, 0.10) | -0.09 (-0.27, 0.10) | ||
| p = 0.30 | p = 0.36 | p = 0.37 | |||
| Country: Va. × Site: rural × Religion: CC | -0.02 (-0.22, 0.19) | 0.05 (-0.15, 0.26) | 0.08 (-0.13, 0.29) | ||
| p = 0.89 | p = 0.61 | p = 0.46 | |||
| Country: Gh. × Porosity Vignettes:Sensed presence | 0.06 (-0.13, 0.25) | 0.06 (-0.13, 0.25) | |||
| p = 0.55 | p = 0.53 | ||||
| Country: Th. × Porosity Vignettes:Sensed presence | -0.02 (-0.27, 0.22) | -0.04 (-0.29, 0.21) | |||
| p = 0.87 | p = 0.75 | ||||
| Country: Ch. × Porosity Vignettes:Sensed presence | 0.07 (-0.17, 0.31) | 0.11 (-0.13, 0.35) | |||
| p = 0.56 | p = 0.37 | ||||
| Country: Va. × Porosity Vignettes:Sensed presence | -0.16 (-0.57, 0.25) | -0.20 (-0.60, 0.21) | |||
| p = 0.46 | p = 0.35 | ||||
| Constant | -0.01 (-0.12, 0.09) | -0.01 (-0.12, 0.09) | 0.004 (-0.09, 0.10) | 0.05 (-0.06, 0.16) | 0.11 (-0.02, 0.24) |
| p = 0.80 | p = 0.79 | p = 0.93 | p = 0.42 | p = 0.12 | |
| Observations | 301 | 297 | 301 | 297 | 293 |
| R2 | 0.07 | 0.17 | 0.46 | 0.51 | 0.53 |
| Adjusted R2 | 0.06 | 0.16 | 0.41 | 0.45 | 0.46 |
| Residual Std. Error | 0.95 (df = 299) | 0.91 (df = 293) | 0.76 (df = 276) | 0.74 (df = 262) | 0.73 (df = 255) |
| F Statistic | 21.55*** (df = 1; 299) | 19.97*** (df = 3; 293) | 9.69*** (df = 24; 276) | 8.00*** (df = 34; 262) | 7.69*** (df = 37; 255) |
table_s20_subscales_MR6 <- stargazer(#r104_spev,
r105_spev_MR6, r106_spev_MR6,
#r107_spev,
r108_spev_MR6, r109_spev_MR6, r110_spev_MR6,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Porosity Vignettes`$",
"^`Altered states of consciousness \\(b\\)`$",
"^`Porosity Vignettes`:`Altered states of consciousness \\(b\\)`$"),
dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s20_subscales_MR6),
file = "./stargazer_tables/table_s20_subscales_MR6.html")
htmltools::includeHTML("./stargazer_tables/table_s20_subscales_MR6.html")
| (1) | (2) | (3) | (4) | (5) | |
| Porosity Vignettes | 0.33 (0.22, 0.43) | 0.32 (0.18, 0.46) | 0.29 (0.15, 0.44) | ||
| p = 0.00 | p = 0.00002 | p = 0.0001 | |||
| Altered states of consciousness (b) | 0.18 (0.07, 0.29) | 0.12 (0.02, 0.23) | 0.19 (0.10, 0.29) | 0.16 (0.05, 0.28) | 0.17 (0.06, 0.29) |
| p = 0.002 | p = 0.03 | p = 0.0001 | p = 0.01 | p = 0.004 | |
| Porosity Vignettes:Altered states of consciousness (b) | -0.02 (-0.13, 0.09) | 0.03 (-0.14, 0.20) | 0.03 (-0.15, 0.20) | ||
| p = 0.71 | p = 0.75 | p = 0.77 | |||
| Country: Gh. | 0.15 (-0.02, 0.31) | 0.07 (-0.16, 0.31) | 0.08 (-0.16, 0.32) | ||
| p = 0.10 | p = 0.54 | p = 0.53 | |||
| Country: Th. | -0.07 (-0.28, 0.15) | -0.13 (-0.36, 0.10) | -0.14 (-0.38, 0.10) | ||
| p = 0.55 | p = 0.28 | p = 0.25 | |||
| Country: Ch. | -0.42 (-0.62, -0.23) | -0.26 (-0.54, 0.02) | -0.26 (-0.54, 0.02) | ||
| p = 0.00004 | p = 0.07 | p = 0.07 | |||
| Country: Va. | 0.83 (0.62, 1.05) | 0.71 (0.48, 0.94) | 0.70 (0.44, 0.95) | ||
| p = 0.00 | p = 0.00 | p = 0.0000002 | |||
| Site: rural | 0.03 (-0.07, 0.13) | 0.04 (-0.06, 0.14) | 0.05 (-0.06, 0.17) | ||
| p = 0.54 | p = 0.41 | p = 0.38 | |||
| Religion: CC | 0.25 (0.15, 0.34) | 0.24 (0.14, 0.34) | 0.24 (0.14, 0.34) | ||
| p = 0.000002 | p = 0.000003 | p = 0.000004 | |||
| Gender: male | -0.08 (-0.18, 0.01) | ||||
| p = 0.08 | |||||
| Age | -0.09 (-0.20, 0.01) | ||||
| p = 0.10 | |||||
| Education: at least HS | -0.08 (-0.26, 0.10) | ||||
| p = 0.38 | |||||
| Country: Gh. × Site: rural | -0.27 (-0.44, -0.10) | -0.30 (-0.47, -0.13) | -0.27 (-0.45, -0.09) | ||
| p = 0.002 | p = 0.001 | p = 0.004 | |||
| Country: Th. × Site: rural | -0.06 (-0.28, 0.16) | -0.05 (-0.26, 0.17) | -0.04 (-0.25, 0.18) | ||
| p = 0.60 | p = 0.69 | p = 0.75 | |||
| Country: Ch. × Site: rural | 0.44 (0.24, 0.63) | 0.43 (0.24, 0.62) | 0.41 (0.20, 0.62) | ||
| p = 0.00002 | p = 0.00003 | p = 0.0002 | |||
| Country: Va. × Site: rural | 0.04 (-0.18, 0.25) | 0.07 (-0.16, 0.29) | 0.06 (-0.16, 0.28) | ||
| p = 0.73 | p = 0.56 | p = 0.61 | |||
| Country: Gh. × Religion: CC | -0.17 (-0.34, 0.01) | -0.12 (-0.29, 0.05) | -0.13 (-0.33, 0.08) | ||
| p = 0.07 | p = 0.17 | p = 0.23 | |||
| Country: Th. × Religion: CC | -0.13 (-0.34, 0.08) | -0.18 (-0.39, 0.04) | -0.16 (-0.38, 0.07) | ||
| p = 0.24 | p = 0.11 | p = 0.18 | |||
| Country: Ch. × Religion: CC | -0.08 (-0.28, 0.12) | -0.08 (-0.28, 0.12) | -0.11 (-0.31, 0.09) | ||
| p = 0.45 | p = 0.45 | p = 0.29 | |||
| Country: Va. × Religion: CC | 0.10 (-0.11, 0.32) | 0.13 (-0.09, 0.35) | 0.14 (-0.08, 0.36) | ||
| p = 0.36 | p = 0.27 | p = 0.22 | |||
| Site: rural × Religion: CC | -0.11 (-0.21, -0.01) | -0.10 (-0.20, -0.0001) | -0.12 (-0.22, -0.02) | ||
| p = 0.03 | p = 0.06 | p = 0.02 | |||
| Country: Gh. × Porosity Vignettes | -0.21 (-0.43, -0.003) | -0.20 (-0.41, 0.01) | |||
| p = 0.05 | p = 0.06 | ||||
| Country: Th. × Porosity Vignettes | -0.03 (-0.29, 0.23) | -0.02 (-0.28, 0.23) | |||
| p = 0.82 | p = 0.87 | ||||
| Country: Ch. × Porosity Vignettes | -0.09 (-0.36, 0.18) | -0.06 (-0.34, 0.21) | |||
| p = 0.52 | p = 0.64 | ||||
| Country: Va. × Porosity Vignettes | 0.44 (0.02, 0.87) | 0.40 (-0.02, 0.83) | |||
| p = 0.05 | p = 0.07 | ||||
| Country: Gh. × Altered states of consciousness (b) | 0.03 (-0.15, 0.20) | 0.07 (-0.14, 0.29) | 0.09 (-0.13, 0.30) | ||
| p = 0.76 | p = 0.52 | p = 0.44 | |||
| Country: Th. × Altered states of consciousness (b) | -0.16 (-0.35, 0.04) | -0.16 (-0.37, 0.05) | -0.15 (-0.36, 0.05) | ||
| p = 0.12 | p = 0.13 | p = 0.15 | |||
| Country: Ch. × Altered states of consciousness (b) | 0.08 (-0.11, 0.28) | 0.06 (-0.23, 0.34) | 0.05 (-0.23, 0.34) | ||
| p = 0.41 | p = 0.71 | p = 0.72 | |||
| Country: Va. × Altered states of consciousness (b) | 0.11 (-0.10, 0.31) | 0.06 (-0.15, 0.28) | 0.03 (-0.19, 0.25) | ||
| p = 0.33 | p = 0.58 | p = 0.79 | |||
| Country: Gh. × Site: rural × Religion: CC | -0.12 (-0.29, 0.06) | -0.15 (-0.32, 0.02) | -0.17 (-0.34, 0.01) | ||
| p = 0.19 | p = 0.09 | p = 0.06 | |||
| Country: Th. × Site: rural × Religion: CC | 0.27 (0.06, 0.48) | 0.23 (0.02, 0.44) | 0.24 (0.03, 0.46) | ||
| p = 0.02 | p = 0.04 | p = 0.03 | |||
| Country: Ch. × Site: rural × Religion: CC | -0.12 (-0.31, 0.08) | -0.11 (-0.31, 0.09) | -0.11 (-0.30, 0.09) | ||
| p = 0.24 | p = 0.28 | p = 0.28 | |||
| Country: Va. × Site: rural × Religion: CC | -0.02 (-0.24, 0.19) | 0.03 (-0.19, 0.25) | 0.04 (-0.18, 0.26) | ||
| p = 0.84 | p = 0.77 | p = 0.75 | |||
| Country: Gh. × Porosity Vignettes:Altered states of consciousness (b) | -0.09 (-0.32, 0.14) | -0.11 (-0.33, 0.12) | |||
| p = 0.44 | p = 0.36 | ||||
| Country: Th. × Porosity Vignettes:Altered states of consciousness (b) | -0.16 (-0.50, 0.19) | -0.20 (-0.55, 0.14) | |||
| p = 0.38 | p = 0.25 | ||||
| Country: Ch. × Porosity Vignettes:Altered states of consciousness (b) | -0.02 (-0.30, 0.26) | -0.004 (-0.28, 0.28) | |||
| p = 0.88 | p = 0.98 | ||||
| Country: Va. × Porosity Vignettes:Altered states of consciousness (b) | 0.29 (-0.25, 0.83) | 0.32 (-0.22, 0.86) | |||
| p = 0.30 | p = 0.25 | ||||
| Constant | -0.01 (-0.12, 0.10) | -0.01 (-0.12, 0.10) | 0.02 (-0.08, 0.11) | 0.03 (-0.09, 0.15) | 0.06 (-0.07, 0.20) |
| p = 0.83 | p = 0.85 | p = 0.73 | p = 0.63 | p = 0.37 | |
| Observations | 301 | 297 | 301 | 297 | 293 |
| R2 | 0.03 | 0.14 | 0.42 | 0.47 | 0.49 |
| Adjusted R2 | 0.03 | 0.13 | 0.37 | 0.41 | 0.42 |
| Residual Std. Error | 0.97 (df = 299) | 0.92 (df = 293) | 0.78 (df = 276) | 0.76 (df = 262) | 0.76 (df = 255) |
| F Statistic | 10.32*** (df = 1; 299) | 15.71*** (df = 3; 293) | 8.46*** (df = 24; 276) | 6.93*** (df = 34; 262) | 6.69*** (df = 37; 255) |
# reliability
bind_rows(MR1 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s3_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR1") %>%
pull(question)))),
MR2 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s3_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR2") %>%
pull(question)))),
MR3 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s3_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR3") %>%
pull(question)))),
MR4 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s3_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR4") %>%
pull(question)))),
MR5 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s3_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR5") %>%
pull(question)))),
MR6 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s3_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR6") %>%
pull(question)))))
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
d3_abs_subscales <- d3_abs %>%
rownames_to_column("subject_id") %>%
gather(question, response, -subject_id) %>%
mutate(question = gsub("_abs", "", question)) %>%
left_join(d_all_all_scales %>% distinct(question, factor)) %>%
filter(!is.na(factor)) %>%
mutate(factorlab = recode_factor(factor,
"MR1" = "Synesthesia",
"MR2" = "Aesthetic involvement in nature",
"MR3" = "Altered states of consciousness (a)",
"MR4" = "Imaginative involvement",
"MR5" = "Sensed presence",
"MR6" = "Altered states of consciousness (b)")) %>%
group_by(subject_id, factor, factorlab) %>%
summarise(score = mean(response, na.rm = T)) %>%
ungroup() %>%
mutate(subject_id = as.numeric(subject_id)) %>%
left_join(d3 %>% distinct(subject_id, country)) %>%
group_by(country, factor, factorlab) %>%
mutate(score = scale(score)) %>%
ungroup() %>%
select(-country, -factor) %>%
spread(factorlab, score) %>%
mutate_all(as.numeric) %>%
left_join(d3_fortab)
Joining, by = "question"
`summarise()` has grouped output by 'subject_id', 'factor'. You can override using the `.groups` argument.
Joining, by = "subject_id"
Joining, by = "subject_id"
r103_spev_MR1 <- lm(`Spiritual Events` ~ `Synesthesia`,
data = d3_abs_subscales)
r103_spev_MR2 <- lm(`Spiritual Events` ~ `Aesthetic involvement in nature`,
data = d3_abs_subscales)
r103_spev_MR3 <- lm(`Spiritual Events` ~ `Altered states of consciousness (a)`,
data = d3_abs_subscales)
r103_spev_MR4 <- lm(`Spiritual Events` ~ `Imaginative involvement`,
data = d3_abs_subscales)
r103_spev_MR5 <- lm(`Spiritual Events` ~ `Sensed presence`,
data = d3_abs_subscales)
r103_spev_MR6 <- lm(`Spiritual Events` ~ `Altered states of consciousness (b)`,
data = d3_abs_subscales)
r104_spev_MR1 <- lm(`Spiritual Events` ~ Country * `Synesthesia`,
data = d3_abs_subscales)
r104_spev_MR2 <- lm(`Spiritual Events` ~ Country * `Aesthetic involvement in nature`,
data = d3_abs_subscales)
r104_spev_MR3 <- lm(`Spiritual Events` ~ Country * `Altered states of consciousness (a)`,
data = d3_abs_subscales)
r104_spev_MR4 <- lm(`Spiritual Events` ~ Country * `Imaginative involvement`,
data = d3_abs_subscales)
r104_spev_MR5 <- lm(`Spiritual Events` ~ Country * `Sensed presence`,
data = d3_abs_subscales)
r104_spev_MR6 <- lm(`Spiritual Events` ~ Country * `Altered states of consciousness (b)`,
data = d3_abs_subscales)
r105_spev_MR1 <- lm(`Spiritual Events` ~ Country * `Synesthesia`
+ Gender + Age,
data = d3_abs_subscales)
r105_spev_MR2 <- lm(`Spiritual Events` ~ Country * `Aesthetic involvement in nature`
+ Gender + Age,
data = d3_abs_subscales)
r105_spev_MR3 <- lm(`Spiritual Events` ~ Country * `Altered states of consciousness (a)`
+ Gender + Age,
data = d3_abs_subscales)
r105_spev_MR4 <- lm(`Spiritual Events` ~ Country * `Imaginative involvement`
+ Gender + Age,
data = d3_abs_subscales)
r105_spev_MR5 <- lm(`Spiritual Events` ~ Country * `Sensed presence`
+ Gender + Age,
data = d3_abs_subscales)
r105_spev_MR6 <- lm(`Spiritual Events` ~ Country * `Altered states of consciousness (b)`
+ Gender + Age,
data = d3_abs_subscales)
r103_dse_MR1 <- lm(`Daily Spiritual Experiences` ~ `Synesthesia`,
data = d3_abs_subscales)
r103_dse_MR2 <- lm(`Daily Spiritual Experiences` ~ `Aesthetic involvement in nature`,
data = d3_abs_subscales)
r103_dse_MR3 <- lm(`Daily Spiritual Experiences` ~ `Altered states of consciousness (a)`,
data = d3_abs_subscales)
r103_dse_MR4 <- lm(`Daily Spiritual Experiences` ~ `Imaginative involvement`,
data = d3_abs_subscales)
r103_dse_MR5 <- lm(`Daily Spiritual Experiences` ~ `Sensed presence`,
data = d3_abs_subscales)
r103_dse_MR6 <- lm(`Daily Spiritual Experiences` ~ `Altered states of consciousness (b)`,
data = d3_abs_subscales)
r104_dse_MR1 <- lm(`Daily Spiritual Experiences` ~ Country * `Synesthesia`,
data = d3_abs_subscales)
r104_dse_MR2 <- lm(`Daily Spiritual Experiences` ~ Country * `Aesthetic involvement in nature`,
data = d3_abs_subscales)
r104_dse_MR3 <- lm(`Daily Spiritual Experiences` ~ Country * `Altered states of consciousness (a)`,
data = d3_abs_subscales)
r104_dse_MR4 <- lm(`Daily Spiritual Experiences` ~ Country * `Imaginative involvement`,
data = d3_abs_subscales)
r104_dse_MR5 <- lm(`Daily Spiritual Experiences` ~ Country * `Sensed presence`,
data = d3_abs_subscales)
r104_dse_MR6 <- lm(`Daily Spiritual Experiences` ~ Country * `Altered states of consciousness (b)`,
data = d3_abs_subscales)
r105_dse_MR1 <- lm(`Daily Spiritual Experiences` ~ Country * `Synesthesia`
+ Gender + Age,
data = d3_abs_subscales)
r105_dse_MR2 <- lm(`Daily Spiritual Experiences` ~ Country * `Aesthetic involvement in nature`
+ Gender + Age,
data = d3_abs_subscales)
r105_dse_MR3 <- lm(`Daily Spiritual Experiences` ~ Country * `Altered states of consciousness (a)`
+ Gender + Age,
data = d3_abs_subscales)
r105_dse_MR4 <- lm(`Daily Spiritual Experiences` ~ Country * `Imaginative involvement`
+ Gender + Age,
data = d3_abs_subscales)
r105_dse_MR5 <- lm(`Daily Spiritual Experiences` ~ Country * `Sensed presence`
+ Gender + Age,
data = d3_abs_subscales)
r105_dse_MR6 <- lm(`Daily Spiritual Experiences` ~ Country * `Altered states of consciousness (b)`
+ Gender + Age,
data = d3_abs_subscales)
table_s32_subscales <- stargazer(
r103_spev_MR1, r103_spev_MR2, r103_spev_MR3, r103_spev_MR4, r103_spev_MR5, r103_spev_MR6,
r104_spev_MR1, r104_spev_MR2, r104_spev_MR3, r104_spev_MR4, r104_spev_MR5, r104_spev_MR6,
r105_spev_MR1, r105_spev_MR2, r105_spev_MR3, r105_spev_MR4, r105_spev_MR5, r105_spev_MR6,
r103_dse_MR1, r103_dse_MR2, r103_dse_MR3, r103_dse_MR4, r103_dse_MR5, r103_dse_MR6,
r104_dse_MR1, r104_dse_MR2, r104_dse_MR3, r104_dse_MR4, r104_dse_MR5, r104_dse_MR6,
r105_dse_MR1, r105_dse_MR2, r105_dse_MR3, r105_dse_MR4, r105_dse_MR5, r105_dse_MR6,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Synesthesia`$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales),
file = "./stargazer_tables/table_s32_subscales.html")
# htmltools::includeHTML("./stargazer_tables/table_s32_subscales.html")
table_s32_subscales_MR1 <- stargazer(r103_spev_MR1, r104_spev_MR1, r105_spev_MR1,
r103_dse_MR1, r104_dse_MR1, r105_dse_MR1,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales_MR1),
file = "./stargazer_tables/table_s32_subscales_MR1.html")
htmltools::includeHTML("./stargazer_tables/table_s32_subscales_MR1.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Synesthesia | 0.20 (0.12, 0.29) | 0.20 (0.14, 0.27) | 0.20 (0.13, 0.26) | 0.09 (0.004, 0.18) | 0.09 (0.03, 0.15) | 0.08 (0.02, 0.14) |
| p = 0.000005 | p = 0.00 | p = 0.00000002 | p = 0.05 | p = 0.01 | p = 0.01 | |
| Country: Gh. | 0.89 (0.75, 1.02) | 0.90 (0.76, 1.03) | 0.87 (0.75, 1.00) | 0.89 (0.76, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.63, -0.37) | -0.48 (-0.62, -0.35) | -0.18 (-0.30, -0.06) | -0.18 (-0.31, -0.06) | ||
| p = 0.00 | p = 0.00 | p = 0.003 | p = 0.005 | |||
| Country: Ch. | -0.67 (-0.80, -0.54) | -0.68 (-0.81, -0.54) | -1.13 (-1.25, -1.01) | -1.14 (-1.26, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.46, 0.72) | 0.52 (0.37, 0.68) | 0.66 (0.53, 0.78) | 0.59 (0.45, 0.73) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.02 (-0.10, 0.05) | -0.07 (-0.13, -0.004) | ||||
| p = 0.50 | p = 0.04 | |||||
| Age | 0.08 (-0.01, 0.16) | 0.09 (0.01, 0.16) | ||||
| p = 0.08 | p = 0.03 | |||||
| Country: Gh. × Synesthesia | 0.14 (0.002, 0.27) | 0.14 (0.005, 0.28) | -0.09 (-0.22, 0.03) | -0.09 (-0.22, 0.03) | ||
| p = 0.05 | p = 0.05 | p = 0.15 | p = 0.16 | |||
| Country: Th. × Synesthesia | -0.04 (-0.17, 0.09) | -0.04 (-0.17, 0.10) | 0.10 (-0.02, 0.22) | 0.10 (-0.02, 0.22) | ||
| p = 0.58 | p = 0.60 | p = 0.10 | p = 0.10 | |||
| Country: Ch. × Synesthesia | -0.15 (-0.28, -0.02) | -0.15 (-0.28, -0.01) | -0.08 (-0.20, 0.05) | -0.08 (-0.20, 0.04) | ||
| p = 0.03 | p = 0.04 | p = 0.23 | p = 0.20 | |||
| Country: Va. × Synesthesia | 0.07 (-0.07, 0.20) | 0.05 (-0.09, 0.19) | 0.07 (-0.05, 0.19) | 0.05 (-0.07, 0.18) | ||
| p = 0.32 | p = 0.47 | p = 0.28 | p = 0.39 | |||
| Constant | 0.00 (-0.08, 0.08) | 0.03 (-0.04, 0.09) | 0.02 (-0.04, 0.09) | 0.00 (-0.09, 0.09) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.45 | p = 0.51 | p = 1.00 | p = 0.51 | p = 0.71 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.04 | 0.43 | 0.43 | 0.01 | 0.51 | 0.52 |
| Adjusted R2 | 0.04 | 0.42 | 0.42 | 0.01 | 0.51 | 0.51 |
| Residual Std. Error | 0.98 (df = 517) | 0.76 (df = 509) | 0.77 (df = 501) | 1.00 (df = 517) | 0.70 (df = 509) | 0.70 (df = 501) |
| F Statistic | 21.56*** (df = 1; 517) | 42.08*** (df = 9; 509) | 34.12*** (df = 11; 501) | 4.16** (df = 1; 517) | 59.76*** (df = 9; 509) | 49.64*** (df = 11; 501) |
table_s32_subscales_MR2 <- stargazer(r103_spev_MR2, r104_spev_MR2, r105_spev_MR2,
r103_dse_MR2, r104_dse_MR2, r105_dse_MR2,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales_MR2),
file = "./stargazer_tables/table_s32_subscales_MR2.html")
htmltools::includeHTML("./stargazer_tables/table_s32_subscales_MR2.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Aesthetic involvement in nature | 0.14 (0.06, 0.23) | 0.15 (0.08, 0.21) | 0.15 (0.08, 0.21) | 0.14 (0.05, 0.23) | 0.14 (0.08, 0.20) | 0.13 (0.07, 0.19) |
| p = 0.002 | p = 0.00002 | p = 0.00003 | p = 0.002 | p = 0.00001 | p = 0.00002 | |
| Country: Gh. | 0.89 (0.75, 1.02) | 0.90 (0.76, 1.04) | 0.87 (0.75, 1.00) | 0.89 (0.76, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.63, -0.37) | -0.48 (-0.61, -0.34) | -0.18 (-0.30, -0.06) | -0.17 (-0.30, -0.05) | ||
| p = 0.00 | p = 0.00 | p = 0.003 | p = 0.01 | |||
| Country: Ch. | -0.67 (-0.80, -0.54) | -0.68 (-0.81, -0.54) | -1.13 (-1.25, -1.01) | -1.14 (-1.26, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.45, 0.72) | 0.50 (0.34, 0.66) | 0.66 (0.53, 0.78) | 0.58 (0.44, 0.72) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.02 (-0.09, 0.05) | -0.05 (-0.12, 0.01) | ||||
| p = 0.62 | p = 0.11 | |||||
| Age | 0.09 (0.01, 0.17) | 0.09 (0.02, 0.16) | ||||
| p = 0.04 | p = 0.02 | |||||
| Country: Gh. × Aesthetic involvement in nature | 0.21 (0.08, 0.35) | 0.22 (0.08, 0.36) | -0.01 (-0.13, 0.12) | 0.001 (-0.12, 0.12) | ||
| p = 0.003 | p = 0.002 | p = 0.90 | p = 0.99 | |||
| Country: Th. × Aesthetic involvement in nature | -0.07 (-0.20, 0.06) | -0.07 (-0.20, 0.06) | 0.05 (-0.07, 0.17) | 0.05 (-0.07, 0.16) | ||
| p = 0.33 | p = 0.31 | p = 0.43 | p = 0.45 | |||
| Country: Ch. × Aesthetic involvement in nature | -0.08 (-0.21, 0.06) | -0.08 (-0.21, 0.06) | -0.06 (-0.18, 0.06) | -0.06 (-0.18, 0.06) | ||
| p = 0.26 | p = 0.27 | p = 0.33 | p = 0.31 | |||
| Country: Va. × Aesthetic involvement in nature | -0.05 (-0.18, 0.09) | -0.05 (-0.19, 0.09) | -0.07 (-0.19, 0.05) | -0.07 (-0.19, 0.06) | ||
| p = 0.50 | p = 0.48 | p = 0.25 | p = 0.29 | |||
| Constant | 0.00 (-0.09, 0.09) | 0.03 (-0.04, 0.09) | 0.02 (-0.04, 0.09) | 0.00 (-0.09, 0.09) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.46 | p = 0.51 | p = 1.00 | p = 0.51 | p = 0.71 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.02 | 0.41 | 0.42 | 0.02 | 0.52 | 0.53 |
| Adjusted R2 | 0.02 | 0.40 | 0.40 | 0.02 | 0.51 | 0.52 |
| Residual Std. Error | 0.99 (df = 517) | 0.78 (df = 509) | 0.77 (df = 501) | 0.99 (df = 517) | 0.70 (df = 509) | 0.69 (df = 501) |
| F Statistic | 10.89*** (df = 1; 517) | 39.16*** (df = 9; 509) | 32.34*** (df = 11; 501) | 10.17*** (df = 1; 517) | 62.06*** (df = 9; 509) | 51.48*** (df = 11; 501) |
table_s32_subscales_MR3 <- stargazer(r103_spev_MR3, r104_spev_MR3, r105_spev_MR3,
r103_dse_MR3, r104_dse_MR3, r105_dse_MR3,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales_MR3),
file = "./stargazer_tables/table_s32_subscales_MR3.html")
htmltools::includeHTML("./stargazer_tables/table_s32_subscales_MR3.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Altered states of consciousness (a) | 0.20 (0.12, 0.29) | 0.21 (0.14, 0.27) | 0.21 (0.15, 0.28) | 0.13 (0.04, 0.21) | 0.13 (0.07, 0.19) | 0.13 (0.07, 0.19) |
| p = 0.000005 | p = 0.00 | p = 0.00 | p = 0.005 | p = 0.00005 | p = 0.00004 | |
| Country: Gh. | 0.89 (0.75, 1.02) | 0.90 (0.76, 1.03) | 0.87 (0.75, 1.00) | 0.89 (0.76, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.63, -0.38) | -0.48 (-0.61, -0.34) | -0.18 (-0.30, -0.06) | -0.17 (-0.30, -0.05) | ||
| p = 0.00 | p = 0.00 | p = 0.003 | p = 0.01 | |||
| Country: Ch. | -0.67 (-0.80, -0.54) | -0.67 (-0.81, -0.54) | -1.13 (-1.25, -1.01) | -1.14 (-1.26, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.46, 0.72) | 0.51 (0.36, 0.66) | 0.66 (0.53, 0.78) | 0.58 (0.44, 0.72) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.01 (-0.08, 0.06) | -0.06 (-0.12, 0.01) | ||||
| p = 0.82 | p = 0.10 | |||||
| Age | 0.07 (-0.01, 0.15) | 0.09 (0.02, 0.16) | ||||
| p = 0.08 | p = 0.02 | |||||
| Country: Gh. × Altered states of consciousness (a) | 0.19 (0.06, 0.33) | 0.18 (0.04, 0.31) | 0.06 (-0.07, 0.18) | 0.05 (-0.08, 0.17) | ||
| p = 0.01 | p = 0.01 | p = 0.37 | p = 0.46 | |||
| Country: Th. × Altered states of consciousness (a) | -0.18 (-0.31, -0.05) | -0.17 (-0.30, -0.04) | -0.07 (-0.18, 0.05) | -0.06 (-0.18, 0.05) | ||
| p = 0.01 | p = 0.01 | p = 0.27 | p = 0.30 | |||
| Country: Ch. × Altered states of consciousness (a) | -0.10 (-0.23, 0.03) | -0.09 (-0.23, 0.04) | -0.05 (-0.17, 0.07) | -0.05 (-0.17, 0.07) | ||
| p = 0.16 | p = 0.17 | p = 0.40 | p = 0.45 | |||
| Country: Va. × Altered states of consciousness (a) | 0.10 (-0.03, 0.24) | 0.11 (-0.02, 0.25) | -0.02 (-0.14, 0.10) | -0.02 (-0.14, 0.10) | ||
| p = 0.14 | p = 0.11 | p = 0.78 | p = 0.75 | |||
| Constant | 0.00 (-0.08, 0.08) | 0.03 (-0.04, 0.09) | 0.02 (-0.04, 0.09) | 0.00 (-0.09, 0.09) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.45 | p = 0.52 | p = 1.00 | p = 0.51 | p = 0.73 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.04 | 0.43 | 0.44 | 0.02 | 0.52 | 0.53 |
| Adjusted R2 | 0.04 | 0.42 | 0.43 | 0.01 | 0.51 | 0.52 |
| Residual Std. Error | 0.98 (df = 517) | 0.76 (df = 509) | 0.76 (df = 501) | 0.99 (df = 517) | 0.70 (df = 509) | 0.70 (df = 501) |
| F Statistic | 21.63*** (df = 1; 517) | 43.53*** (df = 9; 509) | 35.90*** (df = 11; 501) | 8.26*** (df = 1; 517) | 61.05*** (df = 9; 509) | 50.93*** (df = 11; 501) |
table_s32_subscales_MR4 <- stargazer(r103_spev_MR4, r104_spev_MR4, r105_spev_MR4,
r103_dse_MR4, r104_dse_MR4, r105_dse_MR4,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales_MR4),
file = "./stargazer_tables/table_s32_subscales_MR4.html")
htmltools::includeHTML("./stargazer_tables/table_s32_subscales_MR4.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Imaginative involvement | 0.15 (0.07, 0.24) | 0.16 (0.09, 0.23) | 0.16 (0.09, 0.22) | 0.09 (0.004, 0.18) | 0.09 (0.03, 0.15) | 0.09 (0.03, 0.15) |
| p = 0.0005 | p = 0.000004 | p = 0.00001 | p = 0.05 | p = 0.004 | p = 0.005 | |
| Country: Gh. | 0.89 (0.75, 1.02) | 0.90 (0.76, 1.03) | 0.87 (0.75, 1.00) | 0.89 (0.76, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.63, -0.37) | -0.48 (-0.61, -0.34) | -0.18 (-0.30, -0.06) | -0.17 (-0.30, -0.05) | ||
| p = 0.00 | p = 0.00 | p = 0.003 | p = 0.01 | |||
| Country: Ch. | -0.67 (-0.80, -0.54) | -0.68 (-0.81, -0.54) | -1.13 (-1.25, -1.01) | -1.14 (-1.26, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.45, 0.72) | 0.50 (0.34, 0.66) | 0.66 (0.53, 0.78) | 0.57 (0.43, 0.71) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.02 (-0.10, 0.05) | -0.07 (-0.14, -0.01) | ||||
| p = 0.52 | p = 0.03 | |||||
| Age | 0.09 (0.01, 0.18) | 0.11 (0.04, 0.18) | ||||
| p = 0.03 | p = 0.004 | |||||
| Country: Gh. × Imaginative involvement | 0.17 (0.03, 0.31) | 0.17 (0.03, 0.31) | 0.10 (-0.02, 0.23) | 0.10 (-0.02, 0.23) | ||
| p = 0.02 | p = 0.02 | p = 0.11 | p = 0.11 | |||
| Country: Th. × Imaginative involvement | -0.16 (-0.29, -0.03) | -0.15 (-0.28, -0.02) | 0.01 (-0.11, 0.13) | 0.01 (-0.11, 0.13) | ||
| p = 0.02 | p = 0.03 | p = 0.84 | p = 0.85 | |||
| Country: Ch. × Imaginative involvement | 0.03 (-0.10, 0.16) | 0.05 (-0.09, 0.18) | 0.07 (-0.05, 0.19) | 0.09 (-0.03, 0.21) | ||
| p = 0.66 | p = 0.51 | p = 0.26 | p = 0.14 | |||
| Country: Va. × Imaginative involvement | -0.02 (-0.15, 0.12) | -0.04 (-0.18, 0.10) | -0.13 (-0.25, -0.01) | -0.17 (-0.29, -0.04) | ||
| p = 0.83 | p = 0.56 | p = 0.04 | p = 0.01 | |||
| Constant | 0.00 (-0.09, 0.09) | 0.03 (-0.04, 0.09) | 0.02 (-0.04, 0.09) | 0.00 (-0.09, 0.09) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.46 | p = 0.52 | p = 1.00 | p = 0.51 | p = 0.75 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.02 | 0.41 | 0.42 | 0.01 | 0.51 | 0.53 |
| Adjusted R2 | 0.02 | 0.40 | 0.40 | 0.01 | 0.51 | 0.52 |
| Residual Std. Error | 0.99 (df = 517) | 0.77 (df = 509) | 0.77 (df = 501) | 1.00 (df = 517) | 0.70 (df = 509) | 0.70 (df = 501) |
| F Statistic | 12.62*** (df = 1; 517) | 39.63*** (df = 9; 509) | 32.55*** (df = 11; 501) | 4.19** (df = 1; 517) | 60.00*** (df = 9; 509) | 50.51*** (df = 11; 501) |
table_s32_subscales_MR5 <- stargazer(r103_spev_MR5, r104_spev_MR5, r105_spev_MR5,
r103_dse_MR5, r104_dse_MR5, r105_dse_MR5,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales_MR5),
file = "./stargazer_tables/table_s32_subscales_MR5.html")
htmltools::includeHTML("./stargazer_tables/table_s32_subscales_MR5.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Sensed presence | 0.29 (0.21, 0.37) | 0.29 (0.23, 0.36) | 0.29 (0.23, 0.36) | 0.18 (0.09, 0.26) | 0.18 (0.12, 0.24) | 0.18 (0.12, 0.24) |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00005 | p = 0.00 | p = 0.00 | |
| Country: Gh. | 0.89 (0.76, 1.02) | 0.90 (0.77, 1.03) | 0.87 (0.75, 1.00) | 0.89 (0.77, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.63, -0.38) | -0.48 (-0.61, -0.35) | -0.18 (-0.29, -0.06) | -0.17 (-0.29, -0.05) | ||
| p = 0.00 | p = 0.00 | p = 0.003 | p = 0.01 | |||
| Country: Ch. | -0.67 (-0.80, -0.54) | -0.68 (-0.80, -0.55) | -1.13 (-1.25, -1.01) | -1.14 (-1.25, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.46, 0.72) | 0.51 (0.36, 0.66) | 0.66 (0.54, 0.78) | 0.58 (0.44, 0.72) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.02 (-0.09, 0.05) | -0.06 (-0.12, 0.01) | ||||
| p = 0.60 | p = 0.08 | |||||
| Age | 0.08 (0.001, 0.16) | 0.09 (0.02, 0.16) | ||||
| p = 0.05 | p = 0.02 | |||||
| Country: Gh. × Sensed presence | 0.14 (0.01, 0.27) | 0.13 (-0.001, 0.26) | -0.04 (-0.16, 0.09) | -0.05 (-0.17, 0.08) | ||
| p = 0.04 | p = 0.06 | p = 0.56 | p = 0.47 | |||
| Country: Th. × Sensed presence | -0.10 (-0.22, 0.03) | -0.09 (-0.22, 0.03) | 0.04 (-0.07, 0.16) | 0.04 (-0.07, 0.16) | ||
| p = 0.13 | p = 0.15 | p = 0.46 | p = 0.45 | |||
| Country: Ch. × Sensed presence | -0.09 (-0.22, 0.04) | -0.09 (-0.22, 0.04) | 0.004 (-0.12, 0.12) | 0.01 (-0.11, 0.12) | ||
| p = 0.17 | p = 0.18 | p = 0.96 | p = 0.92 | |||
| Country: Va. × Sensed presence | 0.02 (-0.11, 0.15) | 0.02 (-0.11, 0.15) | -0.10 (-0.22, 0.02) | -0.10 (-0.22, 0.02) | ||
| p = 0.80 | p = 0.78 | p = 0.11 | p = 0.12 | |||
| Constant | 0.00 (-0.08, 0.08) | 0.03 (-0.04, 0.09) | 0.02 (-0.04, 0.09) | 0.00 (-0.08, 0.08) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.44 | p = 0.51 | p = 1.00 | p = 0.50 | p = 0.72 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.08 | 0.47 | 0.47 | 0.03 | 0.54 | 0.55 |
| Adjusted R2 | 0.08 | 0.46 | 0.46 | 0.03 | 0.53 | 0.54 |
| Residual Std. Error | 0.96 (df = 517) | 0.74 (df = 509) | 0.74 (df = 501) | 0.98 (df = 517) | 0.69 (df = 509) | 0.68 (df = 501) |
| F Statistic | 46.39*** (df = 1; 517) | 49.59*** (df = 9; 509) | 40.86*** (df = 11; 501) | 17.09*** (df = 1; 517) | 65.34*** (df = 9; 509) | 54.80*** (df = 11; 501) |
table_s32_subscales_MR6 <- stargazer(r103_spev_MR6, r104_spev_MR6, r105_spev_MR6,
r103_dse_MR6, r104_dse_MR6, r105_dse_MR6,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Aesthetic involvement in nature`$",
"^`Altered states of consciousness \\(a\\)`$",
"^`Imaginative involvement`$",
"^`Sensed presence`$",
"^`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s32_subscales_MR6),
file = "./stargazer_tables/table_s32_subscales_MR6.html")
htmltools::includeHTML("./stargazer_tables/table_s32_subscales_MR6.html")
| Spiritual Events | Daily Spiritual Experiences | |||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Altered states of consciousness (b) | 0.28 (0.20, 0.36) | 0.28 (0.22, 0.35) | 0.29 (0.22, 0.35) | 0.17 (0.09, 0.26) | 0.17 (0.11, 0.23) | 0.18 (0.12, 0.24) |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.0001 | p = 0.00000003 | p = 0.00 | |
| Country: Gh. | 0.89 (0.76, 1.02) | 0.90 (0.77, 1.03) | 0.87 (0.75, 1.00) | 0.89 (0.77, 1.01) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Th. | -0.50 (-0.63, -0.38) | -0.49 (-0.62, -0.36) | -0.18 (-0.30, -0.06) | -0.18 (-0.31, -0.06) | ||
| p = 0.00 | p = 0.00 | p = 0.003 | p = 0.004 | |||
| Country: Ch. | -0.67 (-0.80, -0.54) | -0.68 (-0.80, -0.55) | -1.13 (-1.25, -1.01) | -1.14 (-1.26, -1.02) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Country: Va. | 0.59 (0.46, 0.72) | 0.52 (0.38, 0.67) | 0.66 (0.54, 0.78) | 0.59 (0.45, 0.73) | ||
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | |||
| Gender: male | -0.04 (-0.11, 0.03) | -0.08 (-0.14, -0.02) | ||||
| p = 0.26 | p = 0.02 | |||||
| Age | 0.07 (-0.003, 0.15) | 0.09 (0.02, 0.16) | ||||
| p = 0.06 | p = 0.02 | |||||
| Country: Gh. × Altered states of consciousness (b) | 0.10 (-0.03, 0.23) | 0.10 (-0.03, 0.23) | 0.03 (-0.09, 0.15) | 0.02 (-0.10, 0.14) | ||
| p = 0.14 | p = 0.13 | p = 0.66 | p = 0.75 | |||
| Country: Th. × Altered states of consciousness (b) | -0.15 (-0.28, -0.03) | -0.16 (-0.28, -0.03) | 0.04 (-0.07, 0.16) | 0.04 (-0.08, 0.15) | ||
| p = 0.02 | p = 0.02 | p = 0.47 | p = 0.55 | |||
| Country: Ch. × Altered states of consciousness (b) | -0.13 (-0.25, 0.002) | -0.12 (-0.25, 0.01) | -0.06 (-0.18, 0.06) | -0.05 (-0.16, 0.07) | ||
| p = 0.06 | p = 0.07 | p = 0.36 | p = 0.46 | |||
| Country: Va. × Altered states of consciousness (b) | 0.10 (-0.03, 0.23) | 0.09 (-0.04, 0.22) | -0.06 (-0.18, 0.06) | -0.07 (-0.19, 0.05) | ||
| p = 0.14 | p = 0.19 | p = 0.37 | p = 0.27 | |||
| Constant | 0.00 (-0.08, 0.08) | 0.03 (-0.04, 0.09) | 0.02 (-0.04, 0.09) | 0.00 (-0.08, 0.08) | 0.02 (-0.04, 0.08) | 0.01 (-0.05, 0.07) |
| p = 1.00 | p = 0.44 | p = 0.47 | p = 1.00 | p = 0.51 | p = 0.71 | |
| Observations | 519 | 519 | 513 | 519 | 519 | 513 |
| R2 | 0.08 | 0.47 | 0.47 | 0.03 | 0.53 | 0.54 |
| Adjusted R2 | 0.08 | 0.46 | 0.46 | 0.03 | 0.52 | 0.53 |
| Residual Std. Error | 0.96 (df = 517) | 0.74 (df = 509) | 0.74 (df = 501) | 0.99 (df = 517) | 0.69 (df = 509) | 0.69 (df = 501) |
| F Statistic | 43.67*** (df = 1; 517) | 49.83*** (df = 9; 509) | 41.00*** (df = 11; 501) | 16.06*** (df = 1; 517) | 64.32*** (df = 9; 509) | 54.03*** (df = 11; 501) |
# reliability
bind_rows(MR1 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR1") %>%
pull(question)))),
MR2 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR2") %>%
pull(question)))),
MR3 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR3") %>%
pull(question)))),
MR4 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR4") %>%
pull(question)))),
MR5 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR5") %>%
pull(question)))),
MR6 = summary(alpha(d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
column_to_rownames("subject_id") %>%
select(d_all_all_scales %>%
filter(factor == "MR6") %>%
pull(question)))))
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
Reliability analysis
d4_abs_subscales <- d_all_abs %>%
rownames_to_column("subject_id") %>%
filter(grepl("s4_", subject_id)) %>%
gather(question, response, -subject_id) %>%
left_join(d_all_all_scales %>% distinct(question, factor)) %>%
filter(!is.na(factor)) %>%
mutate(factorlab = recode_factor(factor,
"MR1" = "Synesthesia",
"MR2" = "Aesthetic involvement in nature",
"MR3" = "Altered states of consciousness (a)",
"MR4" = "Imaginative involvement",
"MR5" = "Sensed presence",
"MR6" = "Altered states of consciousness (b)")) %>%
group_by(subject_id, factor, factorlab) %>%
summarise(score = mean(response, na.rm = T)) %>%
ungroup() %>%
mutate(subject_id = as.numeric(gsub("s4_", "", subject_id))) %>%
left_join(d4 %>% distinct(subject_id, country)) %>%
group_by(country, factor, factorlab) %>%
mutate(score = scale(score)) %>%
ungroup() %>%
select(-country, -factor) %>%
spread(factorlab, score) %>%
mutate_all(as.numeric) %>%
left_join(d4_fortab_long_spirit)
Joining, by = "question"
`summarise()` has grouped output by 'subject_id', 'factor'. You can override using the `.groups` argument.
Joining, by = "subject_id"
Joining, by = "subject_id"
r105_spirit_MR1 <- lmer(Score ~ Scale * Synesthesia
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r108_spirit_MR1 <- lmer(Score ~ Scale * Country * Synesthesia
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r109_spirit_MR1 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * Synesthesia
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r110_spirit_MR1 <- lmer(Score ~ Scale * Country * `Porosity Scale` * Synesthesia
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r111_spirit_MR1 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * Synesthesia
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r112_spirit_MR1 <- lmer(Score ~ Scale * Country * `Porosity Scale` * Synesthesia
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r105_spirit_MR2 <- lmer(Score ~ Scale * `Aesthetic involvement in nature`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r108_spirit_MR2 <- lmer(Score ~ Scale * Country * `Aesthetic involvement in nature`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r109_spirit_MR2 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Aesthetic involvement in nature`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r110_spirit_MR2 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Aesthetic involvement in nature`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r111_spirit_MR2 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Aesthetic involvement in nature`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r112_spirit_MR2 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Aesthetic involvement in nature`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r105_spirit_MR3 <- lmer(Score ~ Scale * `Altered states of consciousness (a)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r108_spirit_MR3 <- lmer(Score ~ Scale * Country * `Altered states of consciousness (a)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r109_spirit_MR3 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Altered states of consciousness (a)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r110_spirit_MR3 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Altered states of consciousness (a)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r111_spirit_MR3 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Altered states of consciousness (a)`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r112_spirit_MR3 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Altered states of consciousness (a)`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r105_spirit_MR4 <- lmer(Score ~ Scale * `Imaginative involvement`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r108_spirit_MR4 <- lmer(Score ~ Scale * Country * `Imaginative involvement`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r109_spirit_MR4 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Imaginative involvement`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r110_spirit_MR4 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Imaginative involvement`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r111_spirit_MR4 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Imaginative involvement`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r112_spirit_MR4 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Imaginative involvement`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r105_spirit_MR5 <- lmer(Score ~ Scale * `Sensed presence`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r108_spirit_MR5 <- lmer(Score ~ Scale * Country * `Sensed presence`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r109_spirit_MR5 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Sensed presence`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r110_spirit_MR5 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Sensed presence`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r111_spirit_MR5 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Sensed presence`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r112_spirit_MR5 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Sensed presence`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r105_spirit_MR6 <- lmer(Score ~ Scale * `Altered states of consciousness (b)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r108_spirit_MR6 <- lmer(Score ~ Scale * Country * `Altered states of consciousness (b)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r109_spirit_MR6 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Altered states of consciousness (b)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r110_spirit_MR6 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Altered states of consciousness (b)`
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r111_spirit_MR6 <- lmer(Score ~ Scale * Country * `Porosity Vignettes` * `Altered states of consciousness (b)`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
r112_spirit_MR6 <- lmer(Score ~ Scale * Country * `Porosity Scale` * `Altered states of consciousness (b)`
+ Gender + Age
+ (1 | subject_id),
control = lmerControl(optimizer = "bobyqa"),
data = d4_abs_subscales)
table_s40s41_subscales_MR1 <- stargazer(r105_spirit_MR1, r108_spirit_MR1,
r109_spirit_MR1, r110_spirit_MR1,
r111_spirit_MR1, r112_spirit_MR1,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^Synesthesia$",
"^`Porosity Vignettes`$",
"^`Porosity Scale`$",
"^`Porosity Vignettes`:Synesthesia$",
"^`Porosity Scale`:Synesthesia$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40s41_subscales_MR1),
file = "./stargazer_tables/table_s40s41_subscales_MR1.html")
htmltools::includeHTML("./stargazer_tables/table_s40s41_subscales_MR1.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Synesthesia | 0.13 (0.05, 0.21) | 0.13 (0.07, 0.19) | 0.08 (0.02, 0.15) | 0.10 (0.02, 0.18) | 0.07 (0.01, 0.14) | 0.09 (0.01, 0.17) |
| p = 0.002 | p = 0.00001 | p = 0.02 | p = 0.02 | p = 0.04 | p = 0.03 | |
| Porosity Vignettes | 0.24 (0.17, 0.31) | 0.25 (0.18, 0.32) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Scale | 0.35 (0.28, 0.42) | 0.36 (0.28, 0.43) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Vignettes:Synesthesia | -0.002 (-0.07, 0.07) | 0.01 (-0.06, 0.08) | ||||
| p = 0.95 | p = 0.85 | |||||
| Porosity Scale:Synesthesia | -0.05 (-0.12, 0.03) | -0.05 (-0.13, 0.02) | ||||
| p = 0.22 | p = 0.19 | |||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.03, 0.03) | -0.02 (-0.06, 0.02) | -0.01 (-0.06, 0.04) | -0.02 (-0.06, 0.02) | -0.005 (-0.06, 0.05) |
| p = 0.95 | p = 0.98 | p = 0.33 | p = 0.75 | p = 0.37 | p = 0.86 | |
| Country: Gh. | 0.83 (0.71, 0.94) | 0.75 (0.61, 0.88) | 0.63 (0.50, 0.76) | 0.73 (0.59, 0.86) | 0.60 (0.46, 0.73) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Th. | -0.29 (-0.40, -0.18) | -0.29 (-0.40, -0.17) | -0.25 (-0.36, -0.13) | -0.29 (-0.41, -0.17) | -0.24 (-0.36, -0.12) | |
| p = 0.0000003 | p = 0.000001 | p = 0.00004 | p = 0.000001 | p = 0.0002 | ||
| Country: Ch. | -0.86 (-0.98, -0.75) | -0.67 (-0.83, -0.52) | -0.54 (-0.72, -0.37) | -0.65 (-0.81, -0.49) | -0.53 (-0.71, -0.36) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Va. | 0.62 (0.51, 0.74) | 0.51 (0.36, 0.65) | 0.38 (0.19, 0.57) | 0.49 (0.33, 0.64) | 0.35 (0.16, 0.55) | |
| p = 0.00 | p = 0.00 | p = 0.0001 | p = 0.00 | p = 0.0005 | ||
| Gender: male | -0.02 (-0.08, 0.03) | 0.01 (-0.05, 0.07) | ||||
| p = 0.42 | p = 0.72 | |||||
| Age | 0.05 (-0.02, 0.11) | 0.04 (-0.02, 0.11) | ||||
| p = 0.16 | p = 0.17 | |||||
| Scale: Spiritual Events × Country: Gh. | -0.02 (-0.08, 0.05) | -0.04 (-0.12, 0.04) | -0.06 (-0.14, 0.03) | -0.04 (-0.12, 0.05) | -0.06 (-0.15, 0.03) | |
| p = 0.66 | p = 0.37 | p = 0.19 | p = 0.37 | p = 0.18 | ||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.18, -0.05) | -0.09 (-0.16, -0.02) | -0.11 (-0.19, -0.03) | -0.09 (-0.16, -0.02) | -0.12 (-0.19, -0.04) | |
| p = 0.0005 | p = 0.02 | p = 0.005 | p = 0.02 | p = 0.005 | ||
| Scale: Spiritual Events × Country: Ch. | 0.20 (0.13, 0.27) | 0.16 (0.06, 0.26) | 0.12 (0.01, 0.24) | 0.16 (0.06, 0.26) | 0.12 (0.003, 0.24) | |
| p = 0.00 | p = 0.002 | p = 0.04 | p = 0.002 | p = 0.05 | ||
| Scale: Spiritual Events × Country: Va. | -0.14 (-0.21, -0.07) | -0.12 (-0.21, -0.03) | -0.02 (-0.14, 0.11) | -0.12 (-0.22, -0.02) | -0.01 (-0.14, 0.13) | |
| p = 0.0002 | p = 0.01 | p = 0.81 | p = 0.02 | p = 0.94 | ||
| Scale: Spiritual Events × Porosity Vignettes | 0.03 (-0.01, 0.07) | 0.03 (-0.01, 0.08) | ||||
| p = 0.20 | p = 0.19 | |||||
| Country: Gh. × Porosity Vignettes | -0.12 (-0.24, -0.01) | -0.13 (-0.25, -0.01) | ||||
| p = 0.04 | p = 0.04 | |||||
| Country: Th. × Porosity Vignettes | -0.02 (-0.15, 0.11) | -0.03 (-0.16, 0.10) | ||||
| p = 0.78 | p = 0.62 | |||||
| Country: Ch. × Porosity Vignettes | 0.08 (-0.08, 0.25) | 0.07 (-0.10, 0.24) | ||||
| p = 0.33 | p = 0.43 | |||||
| Country: Va. × Porosity Vignettes | -0.14 (-0.29, 0.02) | -0.14 (-0.30, 0.02) | ||||
| p = 0.08 | p = 0.09 | |||||
| Scale: Spiritual Events × Porosity Scale | -0.03 (-0.07, 0.02) | -0.03 (-0.08, 0.02) | ||||
| p = 0.31 | p = 0.29 | |||||
| Country: Gh. × Porosity Scale | -0.09 (-0.22, 0.03) | -0.10 (-0.22, 0.03) | ||||
| p = 0.15 | p = 0.14 | |||||
| Country: Th. × Porosity Scale | -0.02 (-0.15, 0.11) | -0.03 (-0.16, 0.11) | ||||
| p = 0.75 | p = 0.68 | |||||
| Country: Ch. × Porosity Scale | 0.10 (-0.06, 0.26) | 0.08 (-0.08, 0.25) | ||||
| p = 0.24 | p = 0.32 | |||||
| Country: Va. × Porosity Scale | -0.15 (-0.32, 0.03) | -0.15 (-0.33, 0.03) | ||||
| p = 0.11 | p = 0.12 | |||||
| Scale: Spiritual Events:Synesthesia | 0.04 (0.003, 0.07) | 0.04 (0.01, 0.07) | 0.05 (0.01, 0.09) | 0.06 (0.01, 0.12) | 0.05 (0.003, 0.09) | 0.06 (0.01, 0.12) |
| p = 0.04 | p = 0.03 | p = 0.03 | p = 0.02 | p = 0.04 | p = 0.03 | |
| Country: Gh. × Synesthesia | -0.02 (-0.13, 0.10) | 0.09 (-0.04, 0.22) | 0.03 (-0.10, 0.15) | 0.09 (-0.04, 0.22) | 0.03 (-0.10, 0.16) | |
| p = 0.76 | p = 0.19 | p = 0.68 | p = 0.20 | p = 0.67 | ||
| Country: Th. × Synesthesia | -0.09 (-0.20, 0.02) | -0.07 (-0.18, 0.04) | -0.10 (-0.22, 0.03) | -0.06 (-0.18, 0.05) | -0.09 (-0.22, 0.03) | |
| p = 0.10 | p = 0.20 | p = 0.12 | p = 0.26 | p = 0.14 | ||
| Country: Ch. × Synesthesia | -0.06 (-0.18, 0.05) | -0.09 (-0.25, 0.06) | -0.16 (-0.36, 0.03) | -0.09 (-0.25, 0.06) | -0.16 (-0.36, 0.03) | |
| p = 0.27 | p = 0.24 | p = 0.11 | p = 0.25 | p = 0.11 | ||
| Country: Va. × Synesthesia | -0.06 (-0.18, 0.06) | -0.06 (-0.20, 0.08) | 0.09 (-0.12, 0.30) | -0.05 (-0.21, 0.10) | 0.10 (-0.12, 0.31) | |
| p = 0.32 | p = 0.39 | p = 0.41 | p = 0.48 | p = 0.37 | ||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.06 (-0.01, 0.14) | 0.06 (-0.02, 0.14) | ||||
| p = 0.10 | p = 0.12 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.0003 (-0.08, 0.08) | -0.002 (-0.08, 0.08) | ||||
| p = 1.00 | p = 0.97 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.11 (-0.21, 0.001) | -0.11 (-0.21, 0.003) | ||||
| p = 0.06 | p = 0.06 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.02 (-0.11, 0.08) | -0.02 (-0.12, 0.08) | ||||
| p = 0.74 | p = 0.67 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.12 (0.03, 0.20) | 0.12 (0.03, 0.20) | ||||
| p = 0.01 | p = 0.01 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | 0.02 (-0.07, 0.10) | 0.02 (-0.07, 0.11) | ||||
| p = 0.74 | p = 0.73 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.07 (-0.18, 0.04) | -0.06 (-0.18, 0.05) | ||||
| p = 0.22 | p = 0.26 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.09 (-0.21, 0.02) | -0.10 (-0.22, 0.02) | ||||
| p = 0.13 | p = 0.10 | |||||
| Scale: Spiritual Events × Country: Gh. × Synesthesia | 0.04 (-0.03, 0.10) | 0.03 (-0.05, 0.12) | 0.03 (-0.05, 0.12) | 0.04 (-0.05, 0.12) | 0.03 (-0.05, 0.12) | |
| p = 0.32 | p = 0.44 | p = 0.48 | p = 0.42 | p = 0.48 | ||
| Scale: Spiritual Events × Country: Th. × Synesthesia | -0.04 (-0.11, 0.03) | -0.06 (-0.13, 0.02) | -0.05 (-0.13, 0.03) | -0.05 (-0.13, 0.02) | -0.05 (-0.13, 0.04) | |
| p = 0.23 | p = 0.13 | p = 0.26 | p = 0.15 | p = 0.27 | ||
| Scale: Spiritual Events × Country: Ch. × Synesthesia | -0.05 (-0.12, 0.02) | -0.04 (-0.14, 0.06) | -0.03 (-0.16, 0.10) | -0.04 (-0.14, 0.06) | -0.03 (-0.16, 0.11) | |
| p = 0.15 | p = 0.45 | p = 0.68 | p = 0.48 | p = 0.70 | ||
| Scale: Spiritual Events × Country: Va. × Synesthesia | -0.03 (-0.10, 0.04) | 0.003 (-0.09, 0.09) | -0.02 (-0.16, 0.12) | -0.003 (-0.10, 0.09) | -0.03 (-0.18, 0.11) | |
| p = 0.42 | p = 0.96 | p = 0.77 | p = 0.95 | p = 0.67 | ||
| Scale: Spiritual Events × Porosity Vignettes:Synesthesia | -0.01 (-0.05, 0.04) | -0.005 (-0.05, 0.04) | ||||
| p = 0.75 | p = 0.84 | |||||
| Country: Gh. × Porosity Vignettes:Synesthesia | -0.14 (-0.26, -0.02) | -0.14 (-0.27, -0.02) | ||||
| p = 0.03 | p = 0.03 | |||||
| Country: Th. × Porosity Vignettes:Synesthesia | 0.01 (-0.12, 0.14) | -0.002 (-0.14, 0.13) | ||||
| p = 0.88 | p = 0.98 | |||||
| Country: Ch. × Porosity Vignettes:Synesthesia | -0.07 (-0.24, 0.09) | -0.09 (-0.26, 0.08) | ||||
| p = 0.39 | p = 0.29 | |||||
| Country: Va. × Porosity Vignettes:Synesthesia | 0.08 (-0.08, 0.23) | 0.08 (-0.09, 0.24) | ||||
| p = 0.32 | p = 0.38 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes:Synesthesia | -0.04 (-0.12, 0.04) | -0.04 (-0.12, 0.04) | ||||
| p = 0.32 | p = 0.30 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes:Synesthesia | -0.01 (-0.09, 0.08) | -0.01 (-0.10, 0.07) | ||||
| p = 0.83 | p = 0.79 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes:Synesthesia | 0.03 (-0.07, 0.14) | 0.03 (-0.08, 0.14) | ||||
| p = 0.57 | p = 0.60 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes:Synesthesia | -0.06 (-0.16, 0.03) | -0.06 (-0.16, 0.05) | ||||
| p = 0.21 | p = 0.30 | |||||
| Scale: Spiritual Events × Porosity Scale:Synesthesia | 0.01 (-0.04, 0.06) | 0.01 (-0.04, 0.07) | ||||
| p = 0.66 | p = 0.60 | |||||
| Country: Gh. × Porosity Scale:Synesthesia | -0.002 (-0.13, 0.12) | -0.003 (-0.13, 0.12) | ||||
| p = 0.99 | p = 0.97 | |||||
| Country: Th. × Porosity Scale:Synesthesia | -0.03 (-0.18, 0.11) | -0.03 (-0.17, 0.12) | ||||
| p = 0.65 | p = 0.72 | |||||
| Country: Ch. × Porosity Scale:Synesthesia | 0.02 (-0.16, 0.19) | 0.01 (-0.17, 0.18) | ||||
| p = 0.85 | p = 0.93 | |||||
| Country: Va. × Porosity Scale:Synesthesia | -0.08 (-0.27, 0.11) | -0.08 (-0.27, 0.11) | ||||
| p = 0.39 | p = 0.43 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale:Synesthesia | -0.06 (-0.15, 0.02) | -0.07 (-0.15, 0.02) | ||||
| p = 0.14 | p = 0.13 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale:Synesthesia | 0.03 (-0.06, 0.13) | 0.03 (-0.07, 0.13) | ||||
| p = 0.51 | p = 0.55 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale:Synesthesia | 0.02 (-0.10, 0.13) | 0.02 (-0.10, 0.13) | ||||
| p = 0.77 | p = 0.79 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale:Synesthesia | -0.04 (-0.16, 0.09) | -0.03 (-0.16, 0.10) | ||||
| p = 0.57 | p = 0.63 | |||||
| Constant | -0.001 (-0.08, 0.08) | 0.02 (-0.04, 0.07) | 0.06 (-0.004, 0.13) | 0.07 (-0.003, 0.15) | 0.05 (-0.01, 0.12) | 0.08 (0.0002, 0.15) |
| p = 0.98 | p = 0.57 | p = 0.07 | p = 0.06 | p = 0.13 | p = 0.05 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 | 978 |
| Log Likelihood | -1,283.45 | -1,119.01 | -1,111.12 | -1,091.12 | -1,088.93 | -1,072.40 |
| Akaike Inf. Crit. | 2,578.91 | 2,282.02 | 2,306.24 | 2,266.24 | 2,265.86 | 2,232.79 |
| Bayesian Inf. Crit. | 2,608.40 | 2,390.17 | 2,512.70 | 2,472.70 | 2,480.82 | 2,447.75 |
table_s40s41_subscales_MR2 <- stargazer(r105_spirit_MR2, r108_spirit_MR2,
r109_spirit_MR2, r110_spirit_MR2,
r111_spirit_MR2, r112_spirit_MR2,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Aesthetic involvement in nature`$",
"^`Porosity Vignettes`$",
"^`Porosity Scale`$",
"^`Porosity Vignettes`:`Aesthetic involvement in nature`$",
"^`Porosity Scale`:`Aesthetic involvement in nature`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40s41_subscales_MR2),
file = "./stargazer_tables/table_s40s41_subscales_MR2.html")
htmltools::includeHTML("./stargazer_tables/table_s40s41_subscales_MR2.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Aesthetic involvement in nature | 0.05 (-0.03, 0.13) | 0.05 (-0.01, 0.11) | 0.02 (-0.05, 0.09) | 0.001 (-0.08, 0.08) | 0.02 (-0.05, 0.09) | -0.003 (-0.08, 0.07) |
| p = 0.19 | p = 0.09 | p = 0.62 | p = 0.98 | p = 0.65 | p = 0.95 | |
| Porosity Vignettes | 0.27 (0.20, 0.33) | 0.27 (0.20, 0.34) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Scale | 0.36 (0.29, 0.43) | 0.37 (0.30, 0.44) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Vignettes:Aesthetic involvement in nature | -0.08 (-0.15, -0.005) | -0.07 (-0.14, 0.005) | ||||
| p = 0.04 | p = 0.07 | |||||
| Porosity Scale:Aesthetic involvement in nature | -0.001 (-0.08, 0.08) | -0.001 (-0.08, 0.08) | ||||
| p = 0.98 | p = 0.99 | |||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.03, 0.03) | -0.02 (-0.06, 0.02) | -0.005 (-0.05, 0.04) | -0.02 (-0.06, 0.03) | -0.002 (-0.05, 0.05) |
| p = 0.94 | p = 0.98 | p = 0.40 | p = 0.85 | p = 0.44 | p = 0.96 | |
| Country: Gh. | 0.83 (0.71, 0.94) | 0.69 (0.56, 0.81) | 0.62 (0.49, 0.75) | 0.66 (0.53, 0.79) | 0.59 (0.45, 0.72) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Th. | -0.29 (-0.40, -0.17) | -0.29 (-0.40, -0.18) | -0.25 (-0.36, -0.13) | -0.29 (-0.40, -0.17) | -0.23 (-0.36, -0.11) | |
| p = 0.000001 | p = 0.0000005 | p = 0.00004 | p = 0.000002 | p = 0.0002 | ||
| Country: Ch. | -0.86 (-0.98, -0.74) | -0.68 (-0.84, -0.53) | -0.57 (-0.73, -0.40) | -0.66 (-0.82, -0.51) | -0.56 (-0.72, -0.39) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Va. | 0.62 (0.50, 0.74) | 0.50 (0.36, 0.65) | 0.37 (0.17, 0.56) | 0.48 (0.32, 0.64) | 0.34 (0.14, 0.54) | |
| p = 0.00 | p = 0.00 | p = 0.0003 | p = 0.00 | p = 0.001 | ||
| Gender: male | -0.01 (-0.07, 0.05) | 0.02 (-0.03, 0.08) | ||||
| p = 0.85 | p = 0.42 | |||||
| Age | 0.05 (-0.01, 0.12) | 0.04 (-0.02, 0.11) | ||||
| p = 0.12 | p = 0.18 | |||||
| Scale: Spiritual Events × Country: Gh. | -0.02 (-0.08, 0.05) | -0.06 (-0.14, 0.02) | -0.07 (-0.16, 0.01) | -0.06 (-0.15, 0.02) | -0.07 (-0.16, 0.01) | |
| p = 0.66 | p = 0.13 | p = 0.11 | p = 0.13 | p = 0.10 | ||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.18, -0.05) | -0.09 (-0.16, -0.02) | -0.12 (-0.20, -0.04) | -0.09 (-0.17, -0.02) | -0.13 (-0.20, -0.05) | |
| p = 0.001 | p = 0.02 | p = 0.003 | p = 0.02 | p = 0.002 | ||
| Scale: Spiritual Events × Country: Ch. | 0.20 (0.13, 0.27) | 0.16 (0.06, 0.26) | 0.13 (0.02, 0.23) | 0.16 (0.06, 0.26) | 0.12 (0.01, 0.23) | |
| p = 0.00 | p = 0.002 | p = 0.03 | p = 0.002 | p = 0.03 | ||
| Scale: Spiritual Events × Country: Va. | -0.14 (-0.21, -0.07) | -0.12 (-0.21, -0.03) | -0.02 (-0.15, 0.11) | -0.12 (-0.22, -0.02) | -0.01 (-0.14, 0.12) | |
| p = 0.0002 | p = 0.01 | p = 0.77 | p = 0.02 | p = 0.90 | ||
| Scale: Spiritual Events × Porosity Vignettes | 0.04 (-0.004, 0.08) | 0.04 (-0.003, 0.09) | ||||
| p = 0.08 | p = 0.07 | |||||
| Country: Gh. × Porosity Vignettes | -0.11 (-0.23, 0.004) | -0.12 (-0.23, 0.001) | ||||
| p = 0.06 | p = 0.06 | |||||
| Country: Th. × Porosity Vignettes | -0.05 (-0.17, 0.08) | -0.06 (-0.18, 0.07) | ||||
| p = 0.47 | p = 0.37 | |||||
| Country: Ch. × Porosity Vignettes | 0.06 (-0.11, 0.23) | 0.05 (-0.12, 0.22) | ||||
| p = 0.47 | p = 0.57 | |||||
| Country: Va. × Porosity Vignettes | -0.15 (-0.30, 0.001) | -0.15 (-0.31, 0.01) | ||||
| p = 0.06 | p = 0.07 | |||||
| Scale: Spiritual Events × Porosity Scale | -0.01 (-0.06, 0.03) | -0.02 (-0.06, 0.03) | ||||
| p = 0.58 | p = 0.55 | |||||
| Country: Gh. × Porosity Scale | -0.09 (-0.22, 0.04) | -0.09 (-0.22, 0.03) | ||||
| p = 0.16 | p = 0.15 | |||||
| Country: Th. × Porosity Scale | -0.05 (-0.18, 0.09) | -0.05 (-0.19, 0.08) | ||||
| p = 0.49 | p = 0.44 | |||||
| Country: Ch. × Porosity Scale | 0.07 (-0.09, 0.22) | 0.06 (-0.10, 0.21) | ||||
| p = 0.41 | p = 0.49 | |||||
| Country: Va. × Porosity Scale | -0.15 (-0.33, 0.03) | -0.15 (-0.33, 0.04) | ||||
| p = 0.10 | p = 0.12 | |||||
| Scale: Spiritual Events:Aesthetic involvement in nature | 0.02 (-0.02, 0.06) | 0.02 (-0.01, 0.05) | 0.03 (-0.01, 0.08) | 0.04 (-0.01, 0.09) | 0.03 (-0.01, 0.08) | 0.03 (-0.02, 0.09) |
| p = 0.29 | p = 0.25 | p = 0.15 | p = 0.16 | p = 0.16 | p = 0.19 | |
| Country: Gh. × Aesthetic involvement in nature | -0.03 (-0.15, 0.09) | 0.03 (-0.09, 0.16) | 0.03 (-0.10, 0.16) | 0.03 (-0.09, 0.16) | 0.03 (-0.10, 0.16) | |
| p = 0.62 | p = 0.61 | p = 0.69 | p = 0.64 | p = 0.68 | ||
| Country: Th. × Aesthetic involvement in nature | 0.10 (-0.01, 0.22) | 0.12 (0.01, 0.23) | 0.11 (-0.01, 0.23) | 0.12 (0.01, 0.24) | 0.12 (0.01, 0.24) | |
| p = 0.08 | p = 0.05 | p = 0.07 | p = 0.04 | p = 0.05 | ||
| Country: Ch. × Aesthetic involvement in nature | -0.03 (-0.15, 0.09) | -0.05 (-0.22, 0.12) | -0.02 (-0.20, 0.15) | -0.05 (-0.22, 0.12) | -0.02 (-0.20, 0.15) | |
| p = 0.63 | p = 0.56 | p = 0.82 | p = 0.56 | p = 0.80 | ||
| Country: Va. × Aesthetic involvement in nature | -0.08 (-0.20, 0.04) | -0.01 (-0.17, 0.15) | -0.11 (-0.31, 0.09) | -0.02 (-0.19, 0.14) | -0.13 (-0.33, 0.08) | |
| p = 0.21 | p = 0.90 | p = 0.29 | p = 0.79 | p = 0.23 | ||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.07 (-0.003, 0.14) | 0.07 (-0.01, 0.14) | ||||
| p = 0.07 | p = 0.08 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.01 (-0.09, 0.07) | -0.01 (-0.09, 0.07) | ||||
| p = 0.83 | p = 0.79 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.11 (-0.22, -0.01) | -0.11 (-0.22, -0.01) | ||||
| p = 0.04 | p = 0.04 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.03 (-0.13, 0.07) | -0.03 (-0.13, 0.07) | ||||
| p = 0.55 | p = 0.56 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.12 (0.04, 0.20) | 0.12 (0.04, 0.21) | ||||
| p = 0.01 | p = 0.01 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | 0.01 (-0.08, 0.10) | 0.01 (-0.08, 0.10) | ||||
| p = 0.87 | p = 0.86 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.08 (-0.18, 0.03) | -0.07 (-0.18, 0.03) | ||||
| p = 0.15 | p = 0.17 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.11 (-0.22, 0.01) | -0.12 (-0.24, 0.01) | ||||
| p = 0.08 | p = 0.07 | |||||
| Scale: Spiritual Events × Country: Gh. × Aesthetic involvement in nature | 0.03 (-0.04, 0.10) | 0.02 (-0.06, 0.10) | 0.03 (-0.05, 0.12) | 0.02 (-0.06, 0.10) | 0.03 (-0.05, 0.12) | |
| p = 0.39 | p = 0.57 | p = 0.48 | p = 0.57 | p = 0.45 | ||
| Scale: Spiritual Events × Country: Th. × Aesthetic involvement in nature | -0.03 (-0.10, 0.03) | -0.04 (-0.11, 0.03) | -0.04 (-0.11, 0.04) | -0.04 (-0.11, 0.03) | -0.03 (-0.11, 0.05) | |
| p = 0.32 | p = 0.26 | p = 0.38 | p = 0.28 | p = 0.43 | ||
| Scale: Spiritual Events × Country: Ch. × Aesthetic involvement in nature | 0.003 (-0.07, 0.07) | 0.004 (-0.10, 0.11) | 0.03 (-0.09, 0.14) | 0.004 (-0.10, 0.11) | 0.03 (-0.09, 0.14) | |
| p = 0.95 | p = 0.95 | p = 0.67 | p = 0.95 | p = 0.66 | ||
| Scale: Spiritual Events × Country: Va. × Aesthetic involvement in nature | -0.03 (-0.10, 0.05) | 0.02 (-0.08, 0.12) | -0.03 (-0.16, 0.10) | 0.02 (-0.09, 0.13) | -0.04 (-0.17, 0.10) | |
| p = 0.49 | p = 0.70 | p = 0.67 | p = 0.76 | p = 0.57 | ||
| Scale: Spiritual Events × Porosity Vignettes:Aesthetic involvement in nature | -0.004 (-0.05, 0.04) | -0.004 (-0.05, 0.04) | ||||
| p = 0.86 | p = 0.87 | |||||
| Country: Gh. × Porosity Vignettes:Aesthetic involvement in nature | 0.01 (-0.11, 0.13) | 0.004 (-0.12, 0.12) | ||||
| p = 0.90 | p = 0.96 | |||||
| Country: Th. × Porosity Vignettes:Aesthetic involvement in nature | -0.001 (-0.13, 0.13) | -0.01 (-0.14, 0.12) | ||||
| p = 1.00 | p = 0.88 | |||||
| Country: Ch. × Porosity Vignettes:Aesthetic involvement in nature | -0.01 (-0.20, 0.17) | -0.02 (-0.20, 0.16) | ||||
| p = 0.88 | p = 0.83 | |||||
| Country: Va. × Porosity Vignettes:Aesthetic involvement in nature | 0.02 (-0.14, 0.19) | 0.02 (-0.15, 0.18) | ||||
| p = 0.77 | p = 0.86 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes:Aesthetic involvement in nature | -0.01 (-0.09, 0.06) | -0.01 (-0.09, 0.07) | ||||
| p = 0.76 | p = 0.77 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes:Aesthetic involvement in nature | 0.05 (-0.04, 0.13) | 0.05 (-0.04, 0.13) | ||||
| p = 0.28 | p = 0.29 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes:Aesthetic involvement in nature | 0.03 (-0.09, 0.14) | 0.03 (-0.09, 0.14) | ||||
| p = 0.66 | p = 0.67 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes:Aesthetic involvement in nature | -0.08 (-0.18, 0.03) | -0.08 (-0.18, 0.03) | ||||
| p = 0.15 | p = 0.17 | |||||
| Scale: Spiritual Events × Porosity Scale:Aesthetic involvement in nature | 0.02 (-0.03, 0.07) | 0.02 (-0.03, 0.07) | ||||
| p = 0.54 | p = 0.49 | |||||
| Country: Gh. × Porosity Scale:Aesthetic involvement in nature | 0.01 (-0.12, 0.14) | 0.01 (-0.12, 0.14) | ||||
| p = 0.84 | p = 0.89 | |||||
| Country: Th. × Porosity Scale:Aesthetic involvement in nature | -0.02 (-0.16, 0.12) | -0.02 (-0.17, 0.12) | ||||
| p = 0.78 | p = 0.75 | |||||
| Country: Ch. × Porosity Scale:Aesthetic involvement in nature | -0.01 (-0.18, 0.15) | -0.02 (-0.19, 0.14) | ||||
| p = 0.87 | p = 0.78 | |||||
| Country: Va. × Porosity Scale:Aesthetic involvement in nature | 0.09 (-0.11, 0.29) | 0.10 (-0.11, 0.30) | ||||
| p = 0.39 | p = 0.36 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale:Aesthetic involvement in nature | -0.04 (-0.12, 0.05) | -0.04 (-0.13, 0.05) | ||||
| p = 0.39 | p = 0.37 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale:Aesthetic involvement in nature | 0.05 (-0.04, 0.15) | 0.05 (-0.05, 0.14) | ||||
| p = 0.27 | p = 0.31 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale:Aesthetic involvement in nature | 0.02 (-0.09, 0.13) | 0.02 (-0.09, 0.13) | ||||
| p = 0.71 | p = 0.76 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale:Aesthetic involvement in nature | -0.03 (-0.16, 0.11) | -0.02 (-0.15, 0.12) | ||||
| p = 0.71 | p = 0.83 | |||||
| Constant | -0.001 (-0.08, 0.08) | 0.02 (-0.04, 0.07) | 0.07 (0.002, 0.13) | 0.07 (-0.003, 0.14) | 0.06 (-0.004, 0.13) | 0.08 (0.0005, 0.15) |
| p = 0.98 | p = 0.58 | p = 0.05 | p = 0.07 | p = 0.07 | p = 0.05 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 | 978 |
| Log Likelihood | -1,289.22 | -1,138.31 | -1,119.25 | -1,105.08 | -1,097.45 | -1,084.56 |
| Akaike Inf. Crit. | 2,590.44 | 2,320.62 | 2,322.50 | 2,294.16 | 2,282.89 | 2,257.11 |
| Bayesian Inf. Crit. | 2,619.93 | 2,428.77 | 2,528.96 | 2,500.62 | 2,497.86 | 2,472.08 |
table_s40s41_subscales_MR3 <- stargazer(r105_spirit_MR3, r108_spirit_MR3,
r109_spirit_MR3, r110_spirit_MR3,
r111_spirit_MR3, r112_spirit_MR3,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Altered states of consciousness \\(a\\)`$",
"^`Porosity Vignettes`$",
"^`Porosity Scale`$",
"^`Porosity Vignettes`:`Altered states of consciousness \\(a\\)`$",
"^`Porosity Scale`:`Altered states of consciousness \\(a\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40s41_subscales_MR3),
file = "./stargazer_tables/table_s40s41_subscales_MR3.html")
htmltools::includeHTML("./stargazer_tables/table_s40s41_subscales_MR3.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Altered states of consciousness (a) | 0.11 (0.03, 0.19) | 0.10 (0.04, 0.16) | 0.07 (0.001, 0.15) | 0.07 (-0.01, 0.14) | 0.07 (-0.002, 0.15) | 0.07 (-0.01, 0.14) |
| p = 0.01 | p = 0.001 | p = 0.05 | p = 0.09 | p = 0.06 | p = 0.10 | |
| Porosity Vignettes | 0.25 (0.18, 0.32) | 0.25 (0.18, 0.32) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Scale | 0.35 (0.28, 0.42) | 0.36 (0.29, 0.43) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Vignettes:Altered states of consciousness (a) | -0.04 (-0.12, 0.03) | -0.03 (-0.11, 0.04) | ||||
| p = 0.27 | p = 0.39 | |||||
| Porosity Scale:Altered states of consciousness (a) | 0.01 (-0.06, 0.09) | 0.02 (-0.06, 0.09) | ||||
| p = 0.71 | p = 0.63 | |||||
| Scale: Spiritual Events | -0.002 (-0.04, 0.03) | -0.001 (-0.04, 0.03) | -0.01 (-0.06, 0.03) | -0.01 (-0.06, 0.04) | -0.01 (-0.05, 0.03) | -0.004 (-0.05, 0.05) |
| p = 0.94 | p = 0.97 | p = 0.59 | p = 0.78 | p = 0.66 | p = 0.89 | |
| Country: Gh. | 0.83 (0.71, 0.94) | 0.70 (0.57, 0.83) | 0.63 (0.50, 0.76) | 0.68 (0.54, 0.81) | 0.60 (0.46, 0.74) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Th. | -0.29 (-0.40, -0.17) | -0.32 (-0.44, -0.20) | -0.26 (-0.37, -0.14) | -0.32 (-0.45, -0.20) | -0.24 (-0.37, -0.12) | |
| p = 0.000001 | p = 0.0000002 | p = 0.00002 | p = 0.0000005 | p = 0.0002 | ||
| Country: Ch. | -0.86 (-0.98, -0.75) | -0.68 (-0.84, -0.52) | -0.58 (-0.74, -0.42) | -0.66 (-0.82, -0.50) | -0.57 (-0.74, -0.41) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Va. | 0.62 (0.50, 0.74) | 0.51 (0.36, 0.66) | 0.39 (0.19, 0.58) | 0.49 (0.33, 0.66) | 0.36 (0.15, 0.56) | |
| p = 0.00 | p = 0.00 | p = 0.0002 | p = 0.00 | p = 0.001 | ||
| Gender: male | -0.01 (-0.07, 0.04) | 0.02 (-0.03, 0.08) | ||||
| p = 0.63 | p = 0.41 | |||||
| Age | 0.05 (-0.02, 0.11) | 0.04 (-0.02, 0.11) | ||||
| p = 0.16 | p = 0.21 | |||||
| Scale: Spiritual Events × Country: Gh. | -0.02 (-0.08, 0.05) | -0.06 (-0.14, 0.02) | -0.07 (-0.16, 0.01) | -0.06 (-0.15, 0.02) | -0.08 (-0.17, 0.01) | |
| p = 0.65 | p = 0.15 | p = 0.11 | p = 0.14 | p = 0.10 | ||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.18, -0.05) | -0.09 (-0.17, -0.02) | -0.12 (-0.20, -0.04) | -0.10 (-0.17, -0.02) | -0.12 (-0.20, -0.04) | |
| p = 0.001 | p = 0.02 | p = 0.004 | p = 0.02 | p = 0.003 | ||
| Scale: Spiritual Events × Country: Ch. | 0.20 (0.13, 0.27) | 0.16 (0.06, 0.26) | 0.12 (0.01, 0.23) | 0.16 (0.05, 0.26) | 0.12 (0.01, 0.23) | |
| p = 0.00000002 | p = 0.002 | p = 0.04 | p = 0.003 | p = 0.04 | ||
| Scale: Spiritual Events × Country: Va. | -0.14 (-0.21, -0.07) | -0.11 (-0.21, -0.02) | -0.02 (-0.15, 0.11) | -0.11 (-0.21, -0.01) | -0.01 (-0.15, 0.13) | |
| p = 0.0002 | p = 0.03 | p = 0.75 | p = 0.04 | p = 0.90 | ||
| Scale: Spiritual Events × Porosity Vignettes | 0.04 (-0.003, 0.09) | 0.04 (-0.003, 0.09) | ||||
| p = 0.07 | p = 0.07 | |||||
| Country: Gh. × Porosity Vignettes | -0.09 (-0.21, 0.02) | -0.10 (-0.22, 0.02) | ||||
| p = 0.12 | p = 0.11 | |||||
| Country: Th. × Porosity Vignettes | -0.09 (-0.22, 0.05) | -0.10 (-0.24, 0.04) | ||||
| p = 0.21 | p = 0.16 | |||||
| Country: Ch. × Porosity Vignettes | 0.08 (-0.09, 0.25) | 0.07 (-0.10, 0.24) | ||||
| p = 0.34 | p = 0.42 | |||||
| Country: Va. × Porosity Vignettes | -0.15 (-0.31, 0.01) | -0.15 (-0.31, 0.01) | ||||
| p = 0.07 | p = 0.08 | |||||
| Scale: Spiritual Events × Porosity Scale | -0.02 (-0.07, 0.03) | -0.02 (-0.07, 0.03) | ||||
| p = 0.49 | p = 0.44 | |||||
| Country: Gh. × Porosity Scale | -0.08 (-0.21, 0.04) | -0.09 (-0.22, 0.04) | ||||
| p = 0.20 | p = 0.18 | |||||
| Country: Th. × Porosity Scale | -0.04 (-0.18, 0.09) | -0.05 (-0.18, 0.09) | ||||
| p = 0.52 | p = 0.48 | |||||
| Country: Ch. × Porosity Scale | 0.06 (-0.09, 0.22) | 0.05 (-0.11, 0.21) | ||||
| p = 0.44 | p = 0.54 | |||||
| Country: Va. × Porosity Scale | -0.16 (-0.34, 0.02) | -0.15 (-0.33, 0.03) | ||||
| p = 0.09 | p = 0.11 | |||||
| Scale: Spiritual Events:Altered states of consciousness (a) | 0.01 (-0.03, 0.05) | 0.01 (-0.02, 0.04) | 0.02 (-0.03, 0.06) | 0.01 (-0.04, 0.06) | 0.02 (-0.03, 0.06) | 0.01 (-0.04, 0.06) |
| p = 0.58 | p = 0.59 | p = 0.49 | p = 0.67 | p = 0.52 | p = 0.67 | |
| Country: Gh. × Altered states of consciousness (a) | -0.05 (-0.17, 0.07) | 0.04 (-0.09, 0.18) | -0.03 (-0.16, 0.11) | 0.04 (-0.09, 0.18) | -0.02 (-0.16, 0.11) | |
| p = 0.39 | p = 0.55 | p = 0.69 | p = 0.54 | p = 0.75 | ||
| Country: Th. × Altered states of consciousness (a) | 0.07 (-0.04, 0.19) | 0.10 (-0.04, 0.23) | 0.11 (-0.02, 0.23) | 0.10 (-0.04, 0.24) | 0.11 (-0.01, 0.23) | |
| p = 0.19 | p = 0.17 | p = 0.10 | p = 0.16 | p = 0.08 | ||
| Country: Ch. × Altered states of consciousness (a) | -0.03 (-0.15, 0.09) | -0.03 (-0.21, 0.16) | 0.02 (-0.17, 0.20) | -0.03 (-0.22, 0.16) | 0.02 (-0.17, 0.21) | |
| p = 0.63 | p = 0.79 | p = 0.88 | p = 0.74 | p = 0.83 | ||
| Country: Va. × Altered states of consciousness (a) | -0.04 (-0.16, 0.08) | -0.02 (-0.16, 0.13) | -0.07 (-0.25, 0.12) | -0.02 (-0.17, 0.12) | -0.07 (-0.26, 0.11) | |
| p = 0.56 | p = 0.84 | p = 0.49 | p = 0.76 | p = 0.45 | ||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.07 (-0.003, 0.15) | 0.07 (-0.01, 0.15) | ||||
| p = 0.06 | p = 0.07 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.002 (-0.09, 0.08) | -0.003 (-0.09, 0.08) | ||||
| p = 0.97 | p = 0.95 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.11 (-0.22, -0.005) | -0.11 (-0.22, -0.003) | ||||
| p = 0.05 | p = 0.05 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.04 (-0.14, 0.06) | -0.05 (-0.15, 0.06) | ||||
| p = 0.41 | p = 0.36 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.12 (0.03, 0.20) | 0.12 (0.03, 0.21) | ||||
| p = 0.01 | p = 0.01 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | -0.001 (-0.09, 0.09) | 0.00002 (-0.09, 0.09) | ||||
| p = 0.99 | p = 1.00 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.08 (-0.18, 0.02) | -0.08 (-0.18, 0.03) | ||||
| p = 0.13 | p = 0.16 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.10 (-0.22, 0.02) | -0.11 (-0.23, 0.01) | ||||
| p = 0.11 | p = 0.09 | |||||
| Scale: Spiritual Events × Country: Gh. × Altered states of consciousness (a) | 0.004 (-0.07, 0.07) | 0.05 (-0.04, 0.13) | -0.04 (-0.13, 0.05) | 0.05 (-0.04, 0.13) | -0.04 (-0.13, 0.06) | |
| p = 0.93 | p = 0.30 | p = 0.44 | p = 0.30 | p = 0.45 | ||
| Scale: Spiritual Events × Country: Th. × Altered states of consciousness (a) | -0.01 (-0.08, 0.06) | -0.03 (-0.12, 0.05) | 0.003 (-0.08, 0.09) | -0.03 (-0.12, 0.06) | 0.003 (-0.08, 0.09) | |
| p = 0.75 | p = 0.47 | p = 0.94 | p = 0.48 | p = 0.96 | ||
| Scale: Spiritual Events × Country: Ch. × Altered states of consciousness (a) | 0.02 (-0.05, 0.09) | -0.02 (-0.14, 0.10) | 0.06 (-0.06, 0.19) | -0.02 (-0.14, 0.10) | 0.06 (-0.06, 0.19) | |
| p = 0.62 | p = 0.72 | p = 0.33 | p = 0.73 | p = 0.34 | ||
| Scale: Spiritual Events × Country: Va. × Altered states of consciousness (a) | -0.02 (-0.09, 0.05) | 0.02 (-0.07, 0.11) | -0.03 (-0.15, 0.10) | 0.01 (-0.08, 0.11) | -0.02 (-0.15, 0.10) | |
| p = 0.56 | p = 0.73 | p = 0.68 | p = 0.78 | p = 0.71 | ||
| Scale: Spiritual Events × Porosity Vignettes:Altered states of consciousness (a) | -0.04 (-0.09, 0.01) | -0.04 (-0.09, 0.01) | ||||
| p = 0.09 | p = 0.11 | |||||
| Country: Gh. × Porosity Vignettes:Altered states of consciousness (a) | -0.08 (-0.21, 0.04) | -0.08 (-0.20, 0.05) | ||||
| p = 0.19 | p = 0.22 | |||||
| Country: Th. × Porosity Vignettes:Altered states of consciousness (a) | 0.11 (-0.05, 0.27) | 0.11 (-0.06, 0.27) | ||||
| p = 0.18 | p = 0.21 | |||||
| Country: Ch. × Porosity Vignettes:Altered states of consciousness (a) | 0.03 (-0.17, 0.22) | 0.003 (-0.20, 0.20) | ||||
| p = 0.80 | p = 0.98 | |||||
| Country: Va. × Porosity Vignettes:Altered states of consciousness (a) | 0.03 (-0.12, 0.18) | 0.03 (-0.12, 0.19) | ||||
| p = 0.72 | p = 0.68 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes:Altered states of consciousness (a) | -0.05 (-0.13, 0.03) | -0.05 (-0.13, 0.03) | ||||
| p = 0.19 | p = 0.19 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes:Altered states of consciousness (a) | 0.03 (-0.07, 0.13) | 0.03 (-0.07, 0.13) | ||||
| p = 0.57 | p = 0.59 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes:Altered states of consciousness (a) | -0.002 (-0.13, 0.12) | -0.003 (-0.13, 0.12) | ||||
| p = 0.98 | p = 0.97 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes:Altered states of consciousness (a) | -0.04 (-0.14, 0.05) | -0.04 (-0.14, 0.06) | ||||
| p = 0.37 | p = 0.43 | |||||
| Scale: Spiritual Events × Porosity Scale:Altered states of consciousness (a) | 0.02 (-0.03, 0.07) | 0.02 (-0.03, 0.07) | ||||
| p = 0.38 | p = 0.39 | |||||
| Country: Gh. × Porosity Scale:Altered states of consciousness (a) | -0.07 (-0.21, 0.08) | -0.06 (-0.20, 0.09) | ||||
| p = 0.37 | p = 0.44 | |||||
| Country: Th. × Porosity Scale:Altered states of consciousness (a) | 0.06 (-0.08, 0.20) | 0.06 (-0.08, 0.20) | ||||
| p = 0.38 | p = 0.41 | |||||
| Country: Ch. × Porosity Scale:Altered states of consciousness (a) | 0.04 (-0.13, 0.21) | 0.04 (-0.14, 0.21) | ||||
| p = 0.64 | p = 0.68 | |||||
| Country: Va. × Porosity Scale:Altered states of consciousness (a) | 0.04 (-0.12, 0.20) | 0.04 (-0.12, 0.20) | ||||
| p = 0.63 | p = 0.64 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale:Altered states of consciousness (a) | 0.02 (-0.08, 0.12) | 0.02 (-0.08, 0.12) | ||||
| p = 0.68 | p = 0.69 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale:Altered states of consciousness (a) | 0.01 (-0.08, 0.11) | 0.02 (-0.08, 0.11) | ||||
| p = 0.76 | p = 0.72 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale:Altered states of consciousness (a) | 0.02 (-0.10, 0.13) | 0.02 (-0.10, 0.14) | ||||
| p = 0.78 | p = 0.77 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale:Altered states of consciousness (a) | -0.01 (-0.12, 0.10) | -0.01 (-0.12, 0.10) | ||||
| p = 0.85 | p = 0.81 | |||||
| Constant | -0.002 (-0.08, 0.08) | 0.02 (-0.04, 0.07) | 0.07 (0.001, 0.14) | 0.07 (-0.01, 0.14) | 0.06 (-0.01, 0.13) | 0.07 (-0.003, 0.15) |
| p = 0.97 | p = 0.58 | p = 0.05 | p = 0.08 | p = 0.08 | p = 0.07 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 | 978 |
| Log Likelihood | -1,287.18 | -1,135.96 | -1,114.60 | -1,104.26 | -1,093.86 | -1,084.20 |
| Akaike Inf. Crit. | 2,586.37 | 2,315.93 | 2,313.20 | 2,292.53 | 2,275.72 | 2,256.40 |
| Bayesian Inf. Crit. | 2,615.86 | 2,424.07 | 2,519.66 | 2,498.99 | 2,490.68 | 2,471.37 |
table_s40s41_subscales_MR4 <- stargazer(r105_spirit_MR4, r108_spirit_MR4,
r109_spirit_MR4, r110_spirit_MR4,
r111_spirit_MR4, r112_spirit_MR4,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Imaginative involvement`$",
"^`Porosity Vignettes`$",
"^`Porosity Scale`$",
"^`Porosity Vignettes`:`Imaginative involvement`$",
"^`Porosity Scale`:`Imaginative involvement`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40s41_subscales_MR4),
file = "./stargazer_tables/table_s40s41_subscales_MR4.html")
htmltools::includeHTML("./stargazer_tables/table_s40s41_subscales_MR4.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Imaginative involvement | 0.09 (0.01, 0.17) | 0.09 (0.03, 0.15) | 0.08 (0.01, 0.14) | 0.05 (-0.02, 0.12) | 0.08 (0.01, 0.14) | 0.05 (-0.03, 0.13) |
| p = 0.03 | p = 0.004 | p = 0.02 | p = 0.19 | p = 0.03 | p = 0.23 | |
| Porosity Vignettes | 0.26 (0.19, 0.33) | 0.26 (0.19, 0.33) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Scale | 0.36 (0.28, 0.43) | 0.36 (0.29, 0.44) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Vignettes:Imaginative involvement | 0.01 (-0.06, 0.08) | 0.01 (-0.06, 0.09) | ||||
| p = 0.81 | p = 0.75 | |||||
| Porosity Scale:Imaginative involvement | 0.06 (-0.02, 0.13) | 0.06 (-0.01, 0.14) | ||||
| p = 0.13 | p = 0.10 | |||||
| Scale: Spiritual Events | -0.002 (-0.04, 0.03) | -0.0005 (-0.03, 0.03) | -0.02 (-0.06, 0.02) | -0.01 (-0.05, 0.04) | -0.02 (-0.06, 0.02) | -0.003 (-0.05, 0.05) |
| p = 0.94 | p = 0.98 | p = 0.35 | p = 0.84 | p = 0.37 | p = 0.91 | |
| Country: Gh. | 0.83 (0.71, 0.94) | 0.71 (0.58, 0.84) | 0.64 (0.51, 0.77) | 0.69 (0.56, 0.82) | 0.62 (0.48, 0.75) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Th. | -0.29 (-0.40, -0.17) | -0.30 (-0.41, -0.19) | -0.25 (-0.37, -0.13) | -0.30 (-0.42, -0.19) | -0.24 (-0.36, -0.12) | |
| p = 0.000001 | p = 0.0000002 | p = 0.00003 | p = 0.0000003 | p = 0.0002 | ||
| Country: Ch. | -0.86 (-0.98, -0.74) | -0.70 (-0.86, -0.54) | -0.60 (-0.76, -0.43) | -0.68 (-0.84, -0.52) | -0.59 (-0.75, -0.42) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Va. | 0.62 (0.50, 0.74) | 0.51 (0.36, 0.65) | 0.39 (0.19, 0.58) | 0.48 (0.32, 0.63) | 0.36 (0.16, 0.56) | |
| p = 0.00 | p = 0.00 | p = 0.0001 | p = 0.00 | p = 0.0005 | ||
| Gender: male | -0.02 (-0.08, 0.04) | 0.02 (-0.04, 0.08) | ||||
| p = 0.55 | p = 0.51 | |||||
| Age | 0.05 (-0.02, 0.12) | 0.03 (-0.03, 0.10) | ||||
| p = 0.14 | p = 0.31 | |||||
| Scale: Spiritual Events × Country: Gh. | -0.02 (-0.08, 0.05) | -0.06 (-0.14, 0.02) | -0.07 (-0.16, 0.01) | -0.06 (-0.14, 0.03) | -0.08 (-0.16, 0.01) | |
| p = 0.66 | p = 0.18 | p = 0.10 | p = 0.18 | p = 0.10 | ||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.18, -0.05) | -0.09 (-0.16, -0.02) | -0.11 (-0.19, -0.04) | -0.09 (-0.16, -0.02) | -0.12 (-0.20, -0.04) | |
| p = 0.001 | p = 0.01 | p = 0.004 | p = 0.02 | p = 0.004 | ||
| Scale: Spiritual Events × Country: Ch. | 0.20 (0.13, 0.27) | 0.15 (0.05, 0.25) | 0.11 (0.01, 0.22) | 0.15 (0.05, 0.25) | 0.11 (0.001, 0.22) | |
| p = 0.00 | p = 0.003 | p = 0.04 | p = 0.003 | p = 0.05 | ||
| Scale: Spiritual Events × Country: Va. | -0.14 (-0.21, -0.07) | -0.12 (-0.21, -0.03) | -0.01 (-0.14, 0.12) | -0.12 (-0.21, -0.02) | -0.01 (-0.14, 0.12) | |
| p = 0.0002 | p = 0.02 | p = 0.85 | p = 0.02 | p = 0.92 | ||
| Scale: Spiritual Events × Porosity Vignettes | 0.04 (0.00002, 0.09) | 0.05 (0.002, 0.09) | ||||
| p = 0.05 | p = 0.05 | |||||
| Country: Gh. × Porosity Vignettes | -0.11 (-0.23, 0.01) | -0.12 (-0.23, 0.004) | ||||
| p = 0.07 | p = 0.06 | |||||
| Country: Th. × Porosity Vignettes | -0.06 (-0.18, 0.07) | -0.06 (-0.19, 0.06) | ||||
| p = 0.39 | p = 0.32 | |||||
| Country: Ch. × Porosity Vignettes | 0.06 (-0.11, 0.22) | 0.04 (-0.13, 0.21) | ||||
| p = 0.52 | p = 0.63 | |||||
| Country: Va. × Porosity Vignettes | -0.15 (-0.30, -0.001) | -0.15 (-0.31, 0.01) | ||||
| p = 0.05 | p = 0.07 | |||||
| Scale: Spiritual Events × Porosity Scale | -0.01 (-0.06, 0.04) | -0.01 (-0.06, 0.04) | ||||
| p = 0.68 | p = 0.64 | |||||
| Country: Gh. × Porosity Scale | -0.08 (-0.21, 0.05) | -0.09 (-0.22, 0.04) | ||||
| p = 0.21 | p = 0.18 | |||||
| Country: Th. × Porosity Scale | -0.02 (-0.15, 0.11) | -0.03 (-0.16, 0.11) | ||||
| p = 0.74 | p = 0.70 | |||||
| Country: Ch. × Porosity Scale | 0.04 (-0.11, 0.20) | 0.03 (-0.12, 0.19) | ||||
| p = 0.59 | p = 0.68 | |||||
| Country: Va. × Porosity Scale | -0.17 (-0.35, 0.01) | -0.16 (-0.34, 0.02) | ||||
| p = 0.07 | p = 0.08 | |||||
| Scale: Spiritual Events:Imaginative involvement | 0.004 (-0.03, 0.04) | 0.004 (-0.03, 0.04) | 0.01 (-0.03, 0.05) | 0.004 (-0.05, 0.05) | 0.01 (-0.04, 0.05) | 0.002 (-0.05, 0.05) |
| p = 0.84 | p = 0.83 | p = 0.77 | p = 0.89 | p = 0.80 | p = 0.95 | |
| Country: Gh. × Imaginative involvement | -0.01 (-0.12, 0.11) | -0.01 (-0.13, 0.11) | -0.03 (-0.15, 0.09) | -0.001 (-0.12, 0.12) | -0.02 (-0.14, 0.11) | |
| p = 0.91 | p = 0.85 | p = 0.67 | p = 0.99 | p = 0.78 | ||
| Country: Th. × Imaginative involvement | 0.07 (-0.04, 0.19) | 0.09 (-0.02, 0.20) | 0.11 (-0.001, 0.23) | 0.09 (-0.02, 0.20) | 0.11 (-0.003, 0.23) | |
| p = 0.20 | p = 0.13 | p = 0.06 | p = 0.13 | p = 0.06 | ||
| Country: Ch. × Imaginative involvement | 0.02 (-0.10, 0.13) | 0.11 (-0.06, 0.27) | 0.12 (-0.06, 0.29) | 0.11 (-0.05, 0.28) | 0.12 (-0.06, 0.30) | |
| p = 0.78 | p = 0.20 | p = 0.19 | p = 0.19 | p = 0.19 | ||
| Country: Va. × Imaginative involvement | -0.02 (-0.14, 0.10) | -0.01 (-0.14, 0.12) | -0.14 (-0.33, 0.06) | -0.02 (-0.17, 0.12) | -0.17 (-0.38, 0.04) | |
| p = 0.79 | p = 0.86 | p = 0.17 | p = 0.75 | p = 0.13 | ||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.10 (0.03, 0.18) | 0.10 (0.02, 0.18) | ||||
| p = 0.01 | p = 0.01 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.003 (-0.08, 0.07) | -0.01 (-0.09, 0.07) | ||||
| p = 0.95 | p = 0.88 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.14 (-0.24, -0.03) | -0.14 (-0.25, -0.03) | ||||
| p = 0.02 | p = 0.02 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.04 (-0.14, 0.05) | -0.04 (-0.14, 0.06) | ||||
| p = 0.40 | p = 0.42 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.16 (0.07, 0.24) | 0.16 (0.07, 0.25) | ||||
| p = 0.0004 | p = 0.0004 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | 0.004 (-0.08, 0.09) | 0.003 (-0.09, 0.09) | ||||
| p = 0.94 | p = 0.95 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.10 (-0.20, 0.01) | -0.10 (-0.20, 0.01) | ||||
| p = 0.07 | p = 0.08 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.12 (-0.24, -0.003) | -0.13 (-0.25, -0.01) | ||||
| p = 0.05 | p = 0.04 | |||||
| Scale: Spiritual Events × Country: Gh. × Imaginative involvement | -0.08 (-0.14, -0.01) | -0.08 (-0.16, -0.01) | -0.10 (-0.18, -0.02) | -0.08 (-0.16, -0.01) | -0.10 (-0.18, -0.02) | |
| p = 0.04 | p = 0.03 | p = 0.02 | p = 0.04 | p = 0.02 | ||
| Scale: Spiritual Events × Country: Th. × Imaginative involvement | -0.06 (-0.12, 0.01) | -0.05 (-0.12, 0.02) | -0.05 (-0.13, 0.03) | -0.05 (-0.12, 0.02) | -0.05 (-0.13, 0.03) | |
| p = 0.09 | p = 0.16 | p = 0.21 | p = 0.18 | p = 0.24 | ||
| Scale: Spiritual Events × Country: Ch. × Imaginative involvement | 0.07 (0.01, 0.14) | 0.06 (-0.04, 0.16) | 0.12 (0.004, 0.24) | 0.06 (-0.04, 0.17) | 0.12 (0.004, 0.24) | |
| p = 0.04 | p = 0.24 | p = 0.05 | p = 0.25 | p = 0.05 | ||
| Scale: Spiritual Events × Country: Va. × Imaginative involvement | 0.04 (-0.03, 0.11) | 0.06 (-0.02, 0.14) | 0.02 (-0.11, 0.15) | 0.05 (-0.04, 0.14) | 0.01 (-0.13, 0.15) | |
| p = 0.24 | p = 0.16 | p = 0.81 | p = 0.29 | p = 0.93 | ||
| Scale: Spiritual Events × Porosity Vignettes:Imaginative involvement | -0.02 (-0.06, 0.03) | -0.02 (-0.06, 0.03) | ||||
| p = 0.42 | p = 0.52 | |||||
| Country: Gh. × Porosity Vignettes:Imaginative involvement | -0.10 (-0.22, 0.02) | -0.10 (-0.22, 0.02) | ||||
| p = 0.11 | p = 0.12 | |||||
| Country: Th. × Porosity Vignettes:Imaginative involvement | 0.09 (-0.05, 0.22) | 0.08 (-0.05, 0.22) | ||||
| p = 0.22 | p = 0.24 | |||||
| Country: Ch. × Porosity Vignettes:Imaginative involvement | 0.14 (-0.04, 0.32) | 0.12 (-0.06, 0.31) | ||||
| p = 0.14 | p = 0.19 | |||||
| Country: Va. × Porosity Vignettes:Imaginative involvement | -0.01 (-0.16, 0.14) | -0.01 (-0.17, 0.16) | ||||
| p = 0.89 | p = 0.93 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes:Imaginative involvement | -0.10 (-0.18, -0.02) | -0.10 (-0.18, -0.03) | ||||
| p = 0.01 | p = 0.01 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes:Imaginative involvement | 0.07 (-0.01, 0.16) | 0.07 (-0.02, 0.16) | ||||
| p = 0.11 | p = 0.13 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes:Imaginative involvement | -0.01 (-0.12, 0.11) | -0.01 (-0.12, 0.11) | ||||
| p = 0.93 | p = 0.90 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes:Imaginative involvement | -0.03 (-0.12, 0.07) | -0.03 (-0.13, 0.08) | ||||
| p = 0.60 | p = 0.62 | |||||
| Scale: Spiritual Events × Porosity Scale:Imaginative involvement | 0.01 (-0.04, 0.06) | 0.01 (-0.04, 0.06) | ||||
| p = 0.77 | p = 0.75 | |||||
| Country: Gh. × Porosity Scale:Imaginative involvement | -0.13 (-0.26, -0.003) | -0.12 (-0.25, 0.01) | ||||
| p = 0.05 | p = 0.07 | |||||
| Country: Th. × Porosity Scale:Imaginative involvement | 0.05 (-0.08, 0.18) | 0.04 (-0.09, 0.17) | ||||
| p = 0.49 | p = 0.54 | |||||
| Country: Ch. × Porosity Scale:Imaginative involvement | 0.05 (-0.12, 0.22) | 0.04 (-0.13, 0.21) | ||||
| p = 0.56 | p = 0.66 | |||||
| Country: Va. × Porosity Scale:Imaginative involvement | 0.11 (-0.08, 0.30) | 0.11 (-0.08, 0.31) | ||||
| p = 0.27 | p = 0.25 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale:Imaginative involvement | -0.08 (-0.16, 0.003) | -0.08 (-0.17, 0.003) | ||||
| p = 0.06 | p = 0.06 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale:Imaginative involvement | 0.02 (-0.07, 0.11) | 0.02 (-0.07, 0.11) | ||||
| p = 0.65 | p = 0.64 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale:Imaginative involvement | 0.04 (-0.07, 0.15) | 0.03 (-0.08, 0.15) | ||||
| p = 0.53 | p = 0.55 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale:Imaginative involvement | 0.03 (-0.09, 0.16) | 0.03 (-0.10, 0.16) | ||||
| p = 0.63 | p = 0.64 | |||||
| Constant | -0.002 (-0.08, 0.08) | 0.02 (-0.04, 0.07) | 0.07 (0.001, 0.13) | 0.07 (-0.005, 0.14) | 0.06 (-0.01, 0.13) | 0.07 (-0.003, 0.15) |
| p = 0.97 | p = 0.58 | p = 0.05 | p = 0.07 | p = 0.09 | p = 0.06 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 | 978 |
| Log Likelihood | -1,288.13 | -1,132.79 | -1,105.55 | -1,094.29 | -1,083.67 | -1,074.74 |
| Akaike Inf. Crit. | 2,588.25 | 2,309.57 | 2,295.10 | 2,272.58 | 2,255.34 | 2,237.49 |
| Bayesian Inf. Crit. | 2,617.75 | 2,417.72 | 2,501.56 | 2,479.04 | 2,470.30 | 2,452.45 |
table_s40s41_subscales_MR5 <- stargazer(r105_spirit_MR5, r108_spirit_MR5,
r109_spirit_MR5, r110_spirit_MR5,
r111_spirit_MR5, r112_spirit_MR5,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Sensed presence`$",
"^`Porosity Vignettes`$",
"^`Porosity Scale`$",
"^`Porosity Vignettes`:`Sensed presence`$",
"^`Porosity Scale`:`Sensed presence`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40s41_subscales_MR5),
file = "./stargazer_tables/table_s40s41_subscales_MR5.html")
htmltools::includeHTML("./stargazer_tables/table_s40s41_subscales_MR5.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Sensed presence | 0.14 (0.06, 0.22) | 0.14 (0.08, 0.19) | 0.13 (0.07, 0.20) | 0.10 (0.03, 0.17) | 0.14 (0.07, 0.20) | 0.10 (0.03, 0.17) |
| p = 0.001 | p = 0.000004 | p = 0.0001 | p = 0.01 | p = 0.0001 | p = 0.01 | |
| Porosity Vignettes | 0.24 (0.17, 0.31) | 0.24 (0.17, 0.31) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Scale | 0.34 (0.27, 0.41) | 0.34 (0.27, 0.42) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Vignettes:Sensed presence | -0.02 (-0.09, 0.04) | -0.02 (-0.09, 0.05) | ||||
| p = 0.52 | p = 0.58 | |||||
| Porosity Scale:Sensed presence | -0.02 (-0.09, 0.06) | -0.02 (-0.10, 0.05) | ||||
| p = 0.65 | p = 0.59 | |||||
| Scale: Spiritual Events | -0.001 (-0.04, 0.03) | -0.001 (-0.03, 0.03) | -0.02 (-0.06, 0.03) | -0.01 (-0.06, 0.04) | -0.02 (-0.06, 0.03) | -0.004 (-0.05, 0.05) |
| p = 0.94 | p = 0.97 | p = 0.46 | p = 0.83 | p = 0.49 | p = 0.90 | |
| Country: Gh. | 0.83 (0.71, 0.94) | 0.73 (0.60, 0.86) | 0.66 (0.53, 0.80) | 0.70 (0.57, 0.83) | 0.63 (0.49, 0.77) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Th. | -0.29 (-0.40, -0.18) | -0.30 (-0.41, -0.19) | -0.25 (-0.37, -0.14) | -0.31 (-0.42, -0.19) | -0.25 (-0.37, -0.12) | |
| p = 0.0000004 | p = 0.0000001 | p = 0.00002 | p = 0.0000002 | p = 0.0001 | ||
| Country: Ch. | -0.86 (-0.98, -0.75) | -0.71 (-0.87, -0.56) | -0.61 (-0.77, -0.45) | -0.69 (-0.85, -0.53) | -0.60 (-0.76, -0.43) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Va. | 0.62 (0.51, 0.74) | 0.51 (0.37, 0.66) | 0.38 (0.19, 0.58) | 0.48 (0.32, 0.63) | 0.35 (0.16, 0.55) | |
| p = 0.00 | p = 0.00 | p = 0.0001 | p = 0.00 | p = 0.0005 | ||
| Gender: male | -0.02 (-0.08, 0.04) | 0.01 (-0.04, 0.07) | ||||
| p = 0.47 | p = 0.65 | |||||
| Age | 0.07 (0.001, 0.13) | 0.05 (-0.01, 0.11) | ||||
| p = 0.05 | p = 0.13 | |||||
| Scale: Spiritual Events × Country: Gh. | -0.02 (-0.08, 0.05) | -0.07 (-0.15, 0.02) | -0.09 (-0.18, 0.002) | -0.07 (-0.15, 0.02) | -0.09 (-0.18, 0.002) | |
| p = 0.66 | p = 0.13 | p = 0.06 | p = 0.13 | p = 0.06 | ||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.18, -0.05) | -0.11 (-0.18, -0.03) | -0.13 (-0.21, -0.05) | -0.11 (-0.18, -0.03) | -0.13 (-0.21, -0.05) | |
| p = 0.001 | p = 0.004 | p = 0.002 | p = 0.004 | p = 0.002 | ||
| Scale: Spiritual Events × Country: Ch. | 0.20 (0.13, 0.27) | 0.16 (0.06, 0.26) | 0.14 (0.03, 0.25) | 0.16 (0.06, 0.26) | 0.14 (0.02, 0.25) | |
| p = 0.00 | p = 0.002 | p = 0.02 | p = 0.003 | p = 0.02 | ||
| Scale: Spiritual Events × Country: Va. | -0.14 (-0.21, -0.07) | -0.10 (-0.20, -0.01) | -0.01 (-0.14, 0.12) | -0.10 (-0.20, -0.01) | -0.004 (-0.14, 0.13) | |
| p = 0.0002 | p = 0.03 | p = 0.85 | p = 0.04 | p = 0.95 | ||
| Scale: Spiritual Events × Porosity Vignettes | 0.03 (-0.01, 0.08) | 0.04 (-0.01, 0.08) | ||||
| p = 0.13 | p = 0.12 | |||||
| Country: Gh. × Porosity Vignettes | -0.13 (-0.25, -0.02) | -0.13 (-0.25, -0.02) | ||||
| p = 0.03 | p = 0.03 | |||||
| Country: Th. × Porosity Vignettes | -0.05 (-0.17, 0.08) | -0.06 (-0.18, 0.07) | ||||
| p = 0.48 | p = 0.38 | |||||
| Country: Ch. × Porosity Vignettes | 0.06 (-0.11, 0.23) | 0.04 (-0.13, 0.21) | ||||
| p = 0.48 | p = 0.65 | |||||
| Country: Va. × Porosity Vignettes | -0.14 (-0.29, 0.01) | -0.14 (-0.29, 0.02) | ||||
| p = 0.08 | p = 0.09 | |||||
| Scale: Spiritual Events × Porosity Scale | -0.01 (-0.06, 0.03) | -0.02 (-0.06, 0.03) | ||||
| p = 0.58 | p = 0.54 | |||||
| Country: Gh. × Porosity Scale | -0.12 (-0.25, 0.01) | -0.12 (-0.25, 0.01) | ||||
| p = 0.08 | p = 0.08 | |||||
| Country: Th. × Porosity Scale | -0.02 (-0.15, 0.11) | -0.03 (-0.16, 0.11) | ||||
| p = 0.74 | p = 0.69 | |||||
| Country: Ch. × Porosity Scale | 0.04 (-0.11, 0.20) | 0.03 (-0.13, 0.19) | ||||
| p = 0.58 | p = 0.71 | |||||
| Country: Va. × Porosity Scale | -0.15 (-0.33, 0.03) | -0.14 (-0.32, 0.04) | ||||
| p = 0.11 | p = 0.13 | |||||
| Scale: Spiritual Events:Sensed presence | 0.01 (-0.02, 0.05) | 0.01 (-0.02, 0.04) | 0.01 (-0.03, 0.05) | -0.003 (-0.05, 0.05) | 0.01 (-0.03, 0.05) | -0.004 (-0.05, 0.05) |
| p = 0.56 | p = 0.56 | p = 0.58 | p = 0.92 | p = 0.61 | p = 0.87 | |
| Country: Gh. × Sensed presence | 0.04 (-0.07, 0.16) | 0.05 (-0.07, 0.16) | 0.05 (-0.07, 0.17) | 0.05 (-0.07, 0.16) | 0.05 (-0.07, 0.17) | |
| p = 0.49 | p = 0.45 | p = 0.45 | p = 0.45 | p = 0.41 | ||
| Country: Th. × Sensed presence | 0.03 (-0.08, 0.15) | 0.02 (-0.09, 0.13) | 0.04 (-0.07, 0.15) | 0.02 (-0.09, 0.13) | 0.04 (-0.08, 0.15) | |
| p = 0.55 | p = 0.68 | p = 0.50 | p = 0.71 | p = 0.53 | ||
| Country: Ch. × Sensed presence | 0.03 (-0.09, 0.14) | 0.09 (-0.07, 0.26) | 0.06 (-0.10, 0.22) | 0.10 (-0.07, 0.26) | 0.06 (-0.11, 0.22) | |
| p = 0.64 | p = 0.28 | p = 0.47 | p = 0.24 | p = 0.50 | ||
| Country: Va. × Sensed presence | -0.10 (-0.22, 0.01) | -0.08 (-0.22, 0.05) | -0.12 (-0.31, 0.07) | -0.08 (-0.22, 0.07) | -0.10 (-0.30, 0.09) | |
| p = 0.09 | p = 0.22 | p = 0.22 | p = 0.31 | p = 0.31 | ||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.08 (0.01, 0.16) | 0.08 (0.01, 0.16) | ||||
| p = 0.03 | p = 0.04 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.01 (-0.09, 0.07) | -0.01 (-0.09, 0.07) | ||||
| p = 0.74 | p = 0.73 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.12 (-0.23, -0.01) | -0.12 (-0.23, -0.01) | ||||
| p = 0.04 | p = 0.04 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.04 (-0.14, 0.05) | -0.05 (-0.15, 0.05) | ||||
| p = 0.37 | p = 0.35 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.13 (0.05, 0.22) | 0.14 (0.05, 0.22) | ||||
| p = 0.003 | p = 0.003 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | -0.01 (-0.10, 0.08) | -0.01 (-0.10, 0.08) | ||||
| p = 0.88 | p = 0.90 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.07 (-0.18, 0.03) | -0.07 (-0.18, 0.04) | ||||
| p = 0.18 | p = 0.20 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.12 (-0.23, 0.003) | -0.12 (-0.24, 0.001) | ||||
| p = 0.06 | p = 0.06 | |||||
| Scale: Spiritual Events × Country: Gh. × Sensed presence | -0.03 (-0.09, 0.04) | -0.05 (-0.12, 0.03) | -0.05 (-0.13, 0.03) | -0.05 (-0.12, 0.03) | -0.05 (-0.13, 0.03) | |
| p = 0.47 | p = 0.23 | p = 0.22 | p = 0.25 | p = 0.24 | ||
| Scale: Spiritual Events × Country: Th. × Sensed presence | 0.04 (-0.03, 0.11) | 0.05 (-0.02, 0.12) | 0.07 (-0.003, 0.15) | 0.05 (-0.02, 0.12) | 0.07 (-0.003, 0.15) | |
| p = 0.24 | p = 0.19 | p = 0.06 | p = 0.20 | p = 0.06 | ||
| Scale: Spiritual Events × Country: Ch. × Sensed presence | -0.001 (-0.07, 0.07) | -0.03 (-0.13, 0.08) | -0.01 (-0.11, 0.10) | -0.03 (-0.13, 0.08) | -0.01 (-0.12, 0.10) | |
| p = 0.98 | p = 0.60 | p = 0.91 | p = 0.61 | p = 0.93 | ||
| Scale: Spiritual Events × Country: Va. × Sensed presence | 0.01 (-0.06, 0.09) | 0.07 (-0.01, 0.16) | 0.01 (-0.12, 0.14) | 0.07 (-0.03, 0.16) | 0.01 (-0.13, 0.14) | |
| p = 0.70 | p = 0.09 | p = 0.84 | p = 0.16 | p = 0.91 | ||
| Scale: Spiritual Events × Porosity Vignettes:Sensed presence | -0.02 (-0.07, 0.02) | -0.02 (-0.07, 0.02) | ||||
| p = 0.28 | p = 0.33 | |||||
| Country: Gh. × Porosity Vignettes:Sensed presence | -0.06 (-0.18, 0.05) | -0.06 (-0.18, 0.06) | ||||
| p = 0.29 | p = 0.35 | |||||
| Country: Th. × Porosity Vignettes:Sensed presence | 0.08 (-0.04, 0.19) | 0.07 (-0.05, 0.18) | ||||
| p = 0.19 | p = 0.25 | |||||
| Country: Ch. × Porosity Vignettes:Sensed presence | 0.14 (-0.03, 0.31) | 0.12 (-0.05, 0.30) | ||||
| p = 0.12 | p = 0.16 | |||||
| Country: Va. × Porosity Vignettes:Sensed presence | -0.03 (-0.17, 0.11) | -0.04 (-0.18, 0.11) | ||||
| p = 0.66 | p = 0.61 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes:Sensed presence | -0.005 (-0.08, 0.07) | -0.01 (-0.08, 0.07) | ||||
| p = 0.91 | p = 0.88 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes:Sensed presence | 0.11 (0.04, 0.19) | 0.11 (0.04, 0.19) | ||||
| p = 0.002 | p = 0.003 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes:Sensed presence | -0.02 (-0.13, 0.09) | -0.02 (-0.13, 0.09) | ||||
| p = 0.71 | p = 0.71 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes:Sensed presence | -0.10 (-0.19, -0.01) | -0.09 (-0.19, 0.0005) | ||||
| p = 0.04 | p = 0.06 | |||||
| Scale: Spiritual Events × Porosity Scale:Sensed presence | 0.02 (-0.03, 0.07) | 0.02 (-0.03, 0.07) | ||||
| p = 0.45 | p = 0.50 | |||||
| Country: Gh. × Porosity Scale:Sensed presence | -0.06 (-0.19, 0.06) | -0.05 (-0.18, 0.08) | ||||
| p = 0.34 | p = 0.43 | |||||
| Country: Th. × Porosity Scale:Sensed presence | 0.03 (-0.10, 0.17) | 0.04 (-0.10, 0.17) | ||||
| p = 0.65 | p = 0.60 | |||||
| Country: Ch. × Porosity Scale:Sensed presence | 0.07 (-0.08, 0.22) | 0.06 (-0.09, 0.22) | ||||
| p = 0.37 | p = 0.45 | |||||
| Country: Va. × Porosity Scale:Sensed presence | 0.07 (-0.14, 0.27) | 0.05 (-0.16, 0.26) | ||||
| p = 0.53 | p = 0.64 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale:Sensed presence | 0.02 (-0.07, 0.10) | 0.02 (-0.07, 0.11) | ||||
| p = 0.68 | p = 0.66 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale:Sensed presence | 0.08 (-0.01, 0.17) | 0.08 (-0.01, 0.17) | ||||
| p = 0.08 | p = 0.08 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale:Sensed presence | -0.05 (-0.16, 0.05) | -0.05 (-0.16, 0.05) | ||||
| p = 0.30 | p = 0.32 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale:Sensed presence | 0.01 (-0.13, 0.15) | 0.01 (-0.13, 0.15) | ||||
| p = 0.89 | p = 0.94 | |||||
| Constant | -0.001 (-0.08, 0.08) | 0.02 (-0.04, 0.07) | 0.07 (0.004, 0.14) | 0.07 (-0.001, 0.15) | 0.06 (-0.01, 0.13) | 0.07 (-0.0001, 0.15) |
| p = 0.98 | p = 0.58 | p = 0.04 | p = 0.06 | p = 0.08 | p = 0.06 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 | 978 |
| Log Likelihood | -1,284.75 | -1,130.40 | -1,106.45 | -1,094.71 | -1,085.16 | -1,075.08 |
| Akaike Inf. Crit. | 2,581.49 | 2,304.79 | 2,296.91 | 2,273.41 | 2,258.33 | 2,238.15 |
| Bayesian Inf. Crit. | 2,610.99 | 2,412.94 | 2,503.37 | 2,479.87 | 2,473.29 | 2,453.11 |
table_s40s41_subscales_MR6 <- stargazer(r105_spirit_MR6, r108_spirit_MR6,
r109_spirit_MR6, r110_spirit_MR6,
r111_spirit_MR6, r112_spirit_MR6,
type = "html",
ci = T,
report = c("vcsp"),
digits = 2,
digits.extra = 1000,
omit.table.layout = "n",
order = c("^`Altered states of consciousness \\(b\\)`$",
"^`Porosity Vignettes`$",
"^`Porosity Scale`$",
"^`Porosity Vignettes`:`Altered states of consciousness \\(b\\)`$",
"^`Porosity Scale`:`Altered states of consciousness \\(b\\)`$"),
# dep.var.labels.include = F,
dep.var.caption = "",
single.row = T)
cat(sub_interact_fun(table_s40s41_subscales_MR6),
file = "./stargazer_tables/table_s40s41_subscales_MR6.html")
htmltools::includeHTML("./stargazer_tables/table_s40s41_subscales_MR6.html")
| Score | ||||||
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Altered states of consciousness (b) | 0.16 (0.08, 0.24) | 0.16 (0.10, 0.21) | 0.14 (0.07, 0.21) | 0.12 (0.05, 0.19) | 0.14 (0.07, 0.21) | 0.13 (0.05, 0.20) |
| p = 0.0001 | p = 0.0000001 | p = 0.0001 | p = 0.0005 | p = 0.00004 | p = 0.001 | |
| Porosity Vignettes | 0.25 (0.18, 0.32) | 0.25 (0.18, 0.32) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Scale | 0.33 (0.25, 0.40) | 0.33 (0.26, 0.41) | ||||
| p = 0.00 | p = 0.00 | |||||
| Porosity Vignettes:Altered states of consciousness (b) | 0.03 (-0.03, 0.10) | 0.04 (-0.02, 0.11) | ||||
| p = 0.33 | p = 0.22 | |||||
| Porosity Scale:Altered states of consciousness (b) | 0.03 (-0.04, 0.10) | 0.04 (-0.03, 0.11) | ||||
| p = 0.42 | p = 0.32 | |||||
| Scale: Spiritual Events | -0.002 (-0.04, 0.03) | -0.001 (-0.03, 0.03) | -0.02 (-0.07, 0.02) | -0.001 (-0.05, 0.05) | -0.02 (-0.06, 0.02) | 0.003 (-0.05, 0.05) |
| p = 0.94 | p = 0.97 | p = 0.30 | p = 0.97 | p = 0.36 | p = 0.92 | |
| Country: Gh. | 0.83 (0.71, 0.94) | 0.68 (0.56, 0.81) | 0.61 (0.48, 0.74) | 0.67 (0.54, 0.80) | 0.58 (0.45, 0.72) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Th. | -0.29 (-0.40, -0.18) | -0.32 (-0.43, -0.21) | -0.27 (-0.39, -0.15) | -0.32 (-0.44, -0.20) | -0.27 (-0.39, -0.14) | |
| p = 0.0000004 | p = 0.00000003 | p = 0.00001 | p = 0.0000001 | p = 0.00003 | ||
| Country: Ch. | -0.86 (-0.98, -0.75) | -0.65 (-0.80, -0.49) | -0.60 (-0.76, -0.44) | -0.62 (-0.78, -0.46) | -0.59 (-0.75, -0.42) | |
| p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | p = 0.00 | ||
| Country: Va. | 0.62 (0.51, 0.74) | 0.52 (0.37, 0.66) | 0.46 (0.26, 0.66) | 0.50 (0.35, 0.66) | 0.44 (0.24, 0.65) | |
| p = 0.00 | p = 0.00 | p = 0.00001 | p = 0.00 | p = 0.00003 | ||
| Gender: male | -0.02 (-0.08, 0.04) | 0.01 (-0.05, 0.07) | ||||
| p = 0.46 | p = 0.68 | |||||
| Age | 0.05 (-0.01, 0.11) | 0.04 (-0.02, 0.11) | ||||
| p = 0.13 | p = 0.18 | |||||
| Scale: Spiritual Events × Country: Gh. | -0.02 (-0.08, 0.05) | -0.05 (-0.13, 0.03) | -0.07 (-0.15, 0.02) | -0.05 (-0.14, 0.03) | -0.07 (-0.16, 0.02) | |
| p = 0.64 | p = 0.22 | p = 0.13 | p = 0.21 | p = 0.12 | ||
| Scale: Spiritual Events × Country: Th. | -0.12 (-0.18, -0.05) | -0.10 (-0.17, -0.03) | -0.14 (-0.21, -0.06) | -0.10 (-0.17, -0.03) | -0.14 (-0.22, -0.06) | |
| p = 0.0005 | p = 0.01 | p = 0.001 | p = 0.01 | p = 0.001 | ||
| Scale: Spiritual Events × Country: Ch. | 0.20 (0.13, 0.27) | 0.16 (0.06, 0.26) | 0.12 (0.02, 0.23) | 0.16 (0.06, 0.26) | 0.12 (0.01, 0.23) | |
| p = 0.00 | p = 0.002 | p = 0.03 | p = 0.003 | p = 0.04 | ||
| Scale: Spiritual Events × Country: Va. | -0.14 (-0.21, -0.07) | -0.12 (-0.21, -0.02) | 0.02 (-0.12, 0.15) | -0.11 (-0.21, -0.01) | 0.03 (-0.11, 0.17) | |
| p = 0.0002 | p = 0.02 | p = 0.81 | p = 0.03 | p = 0.66 | ||
| Scale: Spiritual Events × Porosity Vignettes | 0.03 (-0.02, 0.07) | 0.03 (-0.02, 0.07) | ||||
| p = 0.21 | p = 0.22 | |||||
| Country: Gh. × Porosity Vignettes | -0.12 (-0.23, 0.001) | -0.12 (-0.24, -0.0005) | ||||
| p = 0.06 | p = 0.05 | |||||
| Country: Th. × Porosity Vignettes | -0.08 (-0.20, 0.05) | -0.09 (-0.21, 0.04) | ||||
| p = 0.24 | p = 0.19 | |||||
| Country: Ch. × Porosity Vignettes | 0.12 (-0.05, 0.29) | 0.10 (-0.07, 0.27) | ||||
| p = 0.18 | p = 0.24 | |||||
| Country: Va. × Porosity Vignettes | -0.16 (-0.31, -0.01) | -0.16 (-0.32, -0.01) | ||||
| p = 0.04 | p = 0.04 | |||||
| Scale: Spiritual Events × Porosity Scale | -0.03 (-0.08, 0.01) | -0.04 (-0.08, 0.01) | ||||
| p = 0.18 | p = 0.17 | |||||
| Country: Gh. × Porosity Scale | -0.07 (-0.19, 0.06) | -0.07 (-0.19, 0.06) | ||||
| p = 0.31 | p = 0.31 | |||||
| Country: Th. × Porosity Scale | -0.02 (-0.16, 0.11) | -0.03 (-0.17, 0.10) | ||||
| p = 0.74 | p = 0.66 | |||||
| Country: Ch. × Porosity Scale | 0.08 (-0.08, 0.23) | 0.07 (-0.09, 0.22) | ||||
| p = 0.33 | p = 0.40 | |||||
| Country: Va. × Porosity Scale | -0.21 (-0.40, -0.03) | -0.22 (-0.40, -0.03) | ||||
| p = 0.03 | p = 0.03 | |||||
| Scale: Spiritual Events:Altered states of consciousness (b) | 0.06 (0.02, 0.09) | 0.06 (0.02, 0.09) | 0.05 (0.01, 0.10) | 0.09 (0.04, 0.14) | 0.05 (0.01, 0.10) | 0.09 (0.04, 0.14) |
| p = 0.002 | p = 0.002 | p = 0.02 | p = 0.0002 | p = 0.02 | p = 0.0002 | |
| Country: Gh. × Altered states of consciousness (b) | -0.07 (-0.18, 0.05) | -0.09 (-0.22, 0.03) | -0.07 (-0.20, 0.05) | -0.09 (-0.22, 0.04) | -0.08 (-0.21, 0.04) | |
| p = 0.24 | p = 0.15 | p = 0.26 | p = 0.17 | p = 0.20 | ||
| Country: Th. × Altered states of consciousness (b) | -0.01 (-0.12, 0.10) | -0.02 (-0.13, 0.09) | -0.01 (-0.12, 0.10) | -0.02 (-0.13, 0.09) | -0.005 (-0.12, 0.11) | |
| p = 0.84 | p = 0.77 | p = 0.90 | p = 0.77 | p = 0.94 | ||
| Country: Ch. × Altered states of consciousness (b) | -0.06 (-0.18, 0.05) | 0.08 (-0.09, 0.24) | -0.01 (-0.17, 0.15) | 0.07 (-0.09, 0.23) | -0.02 (-0.17, 0.14) | |
| p = 0.30 | p = 0.36 | p = 0.91 | p = 0.39 | p = 0.83 | ||
| Country: Va. × Altered states of consciousness (b) | 0.03 (-0.09, 0.15) | 0.11 (-0.03, 0.26) | 0.09 (-0.09, 0.27) | 0.11 (-0.03, 0.26) | 0.09 (-0.08, 0.27) | |
| p = 0.64 | p = 0.14 | p = 0.32 | p = 0.13 | p = 0.31 | ||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes | 0.07 (-0.0001, 0.15) | 0.07 (-0.002, 0.15) | ||||
| p = 0.06 | p = 0.06 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes | -0.01 (-0.09, 0.07) | -0.01 (-0.10, 0.07) | ||||
| p = 0.73 | p = 0.73 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes | -0.11 (-0.22, -0.0005) | -0.11 (-0.22, 0.002) | ||||
| p = 0.05 | p = 0.06 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes | -0.02 (-0.11, 0.08) | -0.03 (-0.13, 0.08) | ||||
| p = 0.75 | p = 0.63 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale | 0.13 (0.05, 0.22) | 0.14 (0.05, 0.22) | ||||
| p = 0.002 | p = 0.002 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale | -0.01 (-0.09, 0.08) | -0.01 (-0.10, 0.08) | ||||
| p = 0.89 | p = 0.90 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale | -0.06 (-0.16, 0.04) | -0.06 (-0.16, 0.05) | ||||
| p = 0.27 | p = 0.31 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale | -0.12 (-0.24, 0.004) | -0.13 (-0.25, -0.01) | ||||
| p = 0.06 | p = 0.05 | |||||
| Scale: Spiritual Events × Country: Gh. × Altered states of consciousness (b) | 0.01 (-0.06, 0.08) | 0.001 (-0.08, 0.08) | 0.01 (-0.07, 0.10) | -0.001 (-0.08, 0.08) | 0.01 (-0.07, 0.10) | |
| p = 0.83 | p = 0.99 | p = 0.75 | p = 0.99 | p = 0.81 | ||
| Scale: Spiritual Events × Country: Th. × Altered states of consciousness (b) | 0.0005 (-0.06, 0.07) | 0.002 (-0.07, 0.07) | -0.02 (-0.09, 0.05) | 0.001 (-0.07, 0.07) | -0.02 (-0.10, 0.05) | |
| p = 0.99 | p = 0.96 | p = 0.63 | p = 0.99 | p = 0.59 | ||
| Scale: Spiritual Events × Country: Ch. × Altered states of consciousness (b) | -0.04 (-0.11, 0.03) | -0.07 (-0.17, 0.04) | -0.06 (-0.16, 0.04) | -0.07 (-0.17, 0.04) | -0.06 (-0.17, 0.04) | |
| p = 0.23 | p = 0.21 | p = 0.26 | p = 0.20 | p = 0.25 | ||
| Scale: Spiritual Events × Country: Va. × Altered states of consciousness (b) | -0.03 (-0.10, 0.04) | 0.03 (-0.06, 0.12) | 0.03 (-0.09, 0.14) | 0.03 (-0.06, 0.13) | 0.03 (-0.09, 0.15) | |
| p = 0.41 | p = 0.55 | p = 0.66 | p = 0.51 | p = 0.66 | ||
| Scale: Spiritual Events × Porosity Vignettes:Altered states of consciousness (b) | -0.01 (-0.05, 0.03) | -0.01 (-0.05, 0.03) | ||||
| p = 0.62 | p = 0.63 | |||||
| Country: Gh. × Porosity Vignettes:Altered states of consciousness (b) | -0.004 (-0.12, 0.12) | -0.01 (-0.14, 0.11) | ||||
| p = 0.96 | p = 0.81 | |||||
| Country: Th. × Porosity Vignettes:Altered states of consciousness (b) | 0.09 (-0.02, 0.21) | 0.08 (-0.03, 0.20) | ||||
| p = 0.11 | p = 0.17 | |||||
| Country: Ch. × Porosity Vignettes:Altered states of consciousness (b) | 0.09 (-0.07, 0.26) | 0.07 (-0.10, 0.24) | ||||
| p = 0.27 | p = 0.43 | |||||
| Country: Va. × Porosity Vignettes:Altered states of consciousness (b) | -0.14 (-0.28, 0.005) | -0.15 (-0.30, -0.01) | ||||
| p = 0.06 | p = 0.04 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Vignettes:Altered states of consciousness (b) | -0.01 (-0.09, 0.07) | -0.01 (-0.09, 0.07) | ||||
| p = 0.83 | p = 0.83 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Vignettes:Altered states of consciousness (b) | 0.06 (-0.01, 0.14) | 0.06 (-0.01, 0.14) | ||||
| p = 0.10 | p = 0.11 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Vignettes:Altered states of consciousness (b) | -0.02 (-0.13, 0.09) | -0.02 (-0.13, 0.09) | ||||
| p = 0.72 | p = 0.74 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Vignettes:Altered states of consciousness (b) | -0.07 (-0.16, 0.02) | -0.07 (-0.17, 0.02) | ||||
| p = 0.13 | p = 0.13 | |||||
| Scale: Spiritual Events × Porosity Scale:Altered states of consciousness (b) | -0.01 (-0.05, 0.04) | -0.004 (-0.05, 0.04) | ||||
| p = 0.75 | p = 0.86 | |||||
| Country: Gh. × Porosity Scale:Altered states of consciousness (b) | 0.004 (-0.12, 0.13) | 0.002 (-0.13, 0.13) | ||||
| p = 0.95 | p = 0.98 | |||||
| Country: Th. × Porosity Scale:Altered states of consciousness (b) | 0.06 (-0.07, 0.18) | 0.05 (-0.07, 0.18) | ||||
| p = 0.39 | p = 0.43 | |||||
| Country: Ch. × Porosity Scale:Altered states of consciousness (b) | 0.04 (-0.11, 0.18) | 0.02 (-0.13, 0.16) | ||||
| p = 0.62 | p = 0.83 | |||||
| Country: Va. × Porosity Scale:Altered states of consciousness (b) | -0.08 (-0.25, 0.09) | -0.09 (-0.26, 0.08) | ||||
| p = 0.34 | p = 0.31 | |||||
| Scale: Spiritual Events × Country: Gh. × Porosity Scale:Altered states of consciousness (b) | -0.08 (-0.16, 0.01) | -0.08 (-0.17, 0.01) | ||||
| p = 0.08 | p = 0.07 | |||||
| Scale: Spiritual Events × Country: Th. × Porosity Scale:Altered states of consciousness (b) | 0.08 (-0.01, 0.16) | 0.07 (-0.01, 0.16) | ||||
| p = 0.07 | p = 0.09 | |||||
| Scale: Spiritual Events × Country: Ch. × Porosity Scale:Altered states of consciousness (b) | 0.02 (-0.08, 0.11) | 0.02 (-0.08, 0.11) | ||||
| p = 0.72 | p = 0.76 | |||||
| Scale: Spiritual Events × Country: Va. × Porosity Scale:Altered states of consciousness (b) | -0.07 (-0.18, 0.04) | -0.07 (-0.19, 0.04) | ||||
| p = 0.21 | p = 0.22 | |||||
| Constant | -0.002 (-0.08, 0.08) | 0.02 (-0.04, 0.07) | 0.07 (0.004, 0.14) | 0.08 (0.004, 0.15) | 0.06 (-0.01, 0.13) | 0.08 (0.01, 0.16) |
| p = 0.98 | p = 0.58 | p = 0.04 | p = 0.04 | p = 0.09 | p = 0.04 | |
| Observations | 1,008 | 1,008 | 1,008 | 1,008 | 978 | 978 |
| Log Likelihood | -1,278.27 | -1,119.88 | -1,109.91 | -1,091.10 | -1,086.86 | -1,070.19 |
| Akaike Inf. Crit. | 2,568.55 | 2,283.76 | 2,303.82 | 2,266.19 | 2,261.72 | 2,228.38 |
| Bayesian Inf. Crit. | 2,598.04 | 2,391.91 | 2,510.28 | 2,472.65 | 2,476.68 | 2,443.34 |